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DOE OSTI2025

FLAMINGO: combining kinetic SZ effect and galaxy–galaxy lensing measurements to gauge the impact of feedback on large-scale structure

Energetic feedback processes associated with accreting supermassive black holes can expel gas from massive haloes and significantly alter various measures of clustering on $\sim$Mpc scales, potentially biasing the values of cosmological parameters inferred from analyses of large-scale structure (LSS) if not modelled accurately. Here, we use the state-of-the-art FLAMINGO suite of cosmological hydrodynamical simulations to gauge the impact of feedback on large-scale structure by comparing to Planck + ACT stacking measurements of the kinetic Sunyaev–Zel’dovich (kSZ) effect of SDSS BOSS galaxies. We make careful like-with-like comparisons to the observations, aided by high precision KiDS and DES galaxy–galaxy lensing measurements of the BOSS galaxies to inform the selection of the simulated galaxies. In qualitative agreement with several recent studies using dark matter only simulations corrected for baryonic effects, we find that the kSZ effect measurements prefer stronger feedback than predicted by simulations which have been calibrated to reproduce the gas fractions of low redshift X-ray-selected groups and clusters. We find that the increased feedback can help to reduce the so-called $S_8$ tension between the observed and CMB-predicted clustering on small scales as probed by cosmic shear (although at the expense of agreement with the X-ray group measurements). However, the increased feedback is only marginally effective at reducing the reported offsets between the predicted and observed clustering as probed by the thermal SZ (tSZ) effect power spectrum and tSZ effect – weak lensing cross-spectrum, both of which are sensitive to higher halo masses than cosmic shear.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Quantifying Uncertainties in Earth's Energy Budget by Cloud Feedback and Ocean Heat Uptake Using E3SM-Slab Ocean Configurations

In order to improve predictive skills of Earth System Model, we need to better understand processes that control Earth's energy budget via ocean, atmosphere, and cryosphere interactions. Simulated energy budget in comprehensive Earth System Models shows a wide range, leading to large uncertainties in predicting Earth system dynamic and thermodynamic variations and associated social-economic impacts. Uncertainties in cloud feedbacks have been identified as the main cause of the large inter-model spread, but oceanic adjustments, especially those associated with ocean heat uptake (OHU) and the Atlantic Meridional Overturning Circulation (AMOC), also play an important role. In this proposed work, we focus on understanding the individual and combined roles of cloud feedbacks and ocean adjustments on modulating Earth's energy balance. This research is motivated by our overarching hypothesis that oceanic adjustment is a key source of uncertainty, in addition to those associated with the cloud feedbacks; further, the ocean adjustment and associated OHU work through the cloud feedbacks to modulate Earth's energy budget and temperature variations. We test this hypothesis using numerical experiments where we systematically enable and disable cloud feedbacks in conjunction with perturbations to OHU.

58 GEOSCIENCES↗

DOE OSTI2025

Bridging Scales in Black Hole Accretion and Feedback: Relativistic Jet Linking the Horizon to the Host Galaxy

Simulating black hole (BH) accretion and feedback from the BH horizon to galactic scales is extremely challenging, as it involves a vast range of scales. Recently, our multizone method has successfully achieved global dynamical steady states of hot accretion flows in 3D general relativistic magnetohydrodynamic simulations by tracking the bidirectional interaction between a nonspinning BH and its host galaxy. In this paper, we present technical improvements to the method and apply it to spin a * = 0.9 BHs, which power relativistic jets. We first test the new multizone setup with a smaller Bondi radius, R B ≈ 400 r g , where r g is the gravitational radius. The strongly magnetized accretion launches a relativistic jet with an intermediate feedback efficiency η ∼ 30%, in between that of a prograde (η ∼ 100%) and retrograde (η ∼ 10%) torus. Interestingly, both prograde and retrograde simulations also eventually converge to the same intermediate efficiency when evolved long enough, as accumulated magnetic fields remove gas rotation. We then extend strongly magnetized simulations to larger Bondi radii, R B ≈ 2 × 10 3 , 2 × 10 4 , 2 × 10 5 r g . We find that the BH accretion rate $\dot{M}$ is suppressed with respect to the Bondi rate as $\dot{M}_{\textrm{B}}$ as $\dot{M}/\dot{M}_{\textrm{B}} ∝ R_{\textrm{B}}^{-1/2}$. However, despite some variability, the time-averaged feedback efficiency remains at η ∼ 30%, independent of R B . This suggests that BH feedback efficiency in hot accretion flows is mainly governed by the BH spin (a * ) rather than by the galactic properties (R B ). From these first-principles simulations, we provide a feedback subgrid prescription for cosmological simulations: $\dot{E}_{\textrm{fb}} = 2$ x $10^{-3}[R_{\textrm{B}}/(2$ x $10^5 r_g)]^{-1/2}$ $\dot{M}_{\textrm{B}}c^2$ for BH spin a * = 0.9.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Deriving Material Properties from Feedback Error Signals in Scanning Tunneling Microscopy

Imperfections in measurements, e.g., deviations and broadening, are not devoid of information; rather, they can reveal valuable physical properties and processes. Scanning tunneling microscopy leverages a negative feedback loop to regulate the tunneling current. Practically, current fluctuates around its set point, and such deviations are considered insignificant and ignored. Here, in this study, we investigate the information embedded in these deviations. In the constant-current mode with an active feedback loop, we observe an unexpected persistent DC current offset from its set point when the tunneling junction is periodically perturbed. We demonstrate both experimentally and theoretically that such error signals encode local tunneling barrier heights and the square of local differential conductance as a consequence of the interplay between rectification and active feedback compensation. We provide evidence on the generalizability of this phenomenology to other negative feedback systems. This new approach has the potential to broadly impact physical sciences by allowing rapid measurements without lock-in amplifiers.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Cloud Feedback Uncertainty in the Equatorial Pacific Across CMIP6 Models

Cloud feedback is the largest uncertainty in estimating Equilibrium Climate Sensitivity. In this study we focus on the equatorial Pacific, where CMIP6 model cloud feedback spread is notably large. Cloud radiative effects in this region are relevant for the global climate. Our findings show that models predict a consistent shift towards the ascent regime in response to El Nino-like sea surface warming. Models diverge in terms of the radiative impact due to differences in cloud characteristics in ascent and subsidence regimes. Using the observed relationship between circulation regime and cloud radiative effect, we find a reduction in the regional mean cloud feedback estimate from 0.77 to 0.22 W m -2 K -1 , though this does not substantially lessen the model spread in total feedback. Pathways to reduce this spread include: improving confidence in the regional ocean warming pattern, and using observations and models to understand cloud type and circulation interactions.

CMIP6↗

DOE OSTI2025

Nonlocal, Pattern-Aware Response and Feedback Framework for Regional Climate Response

We devise a pattern-aware feedback framework for representing the forced climate response using a suite of Green’s function experiments with solar radiation perturbations. By considering the column energy balance, a comprehensive linear response function (CLRF) for important climate variables and feedback quantities such as moist static energy, sea surface temperature, albedo, cloud optical depth, and lapse rate is learned from Green’s function data. The learned CLRF delineates the effects of the energy diffusion in both the ocean and atmosphere and the pattern-aware feedbacks from the aforementioned radiatively active processes. The CLRF can then be decomposed into forcing–response mode pairs, which are in turn used to construct a reduced-order model describing the dominant dynamics of climate responses. These mode pairs capture nonlocal effects and teleconnections in the climate and thus make the reduced-order model apt for capturing regional features of climate response. A key observation is that the CLRF captures the polar-amplified response as the most excitable mode of the climate system, and this mode is explainable in the data-learned pattern-aware feedback framework. The reduced-order model can be used for predicting the response for a given forcing and for reconstructing the forcing from a given response; we demonstrate these capabilities for multiple independent forcing scenarios.

Feedback↗

DOE OSTI2024

Proton Acceleration in Low- β Magnetic Reconnection with Energetic Particle Feedback

Magnetic reconnection regions in space and astrophysics are known as active particle acceleration sites. There is ample evidence showing that energetic particles can take a substantial amount of converted energy during magnetic reconnection. However, there has been a lack of studies understanding the backreaction of energetic particles at magnetohydrodynamical scales in magnetic reconnection. To address this, we have developed a new computational method to explore the feedback by nonthermal energetic particles. This approach considers the backreaction from these energetic particles by incorporating their pressure into magnetohydrodynamics (MHD) equations. The pressure of the energetic particles is evaluated from their distribution evolved through Parker's transport equation, solved using stochastic differential equations (SDEs), so we coin the name MHD-SDE. Applying this method to low-β magnetic reconnection simulations, we find that reconnection is capable of accelerating a large fraction of energetic particles that contain a substantial amount of energy. When the feedback from these particles is included, their pressure suppresses the compression structures generated by magnetic reconnection, thereby mediating particle energization. Consequently, the feedback from energetic particles results in a steeper power-law energy spectrum. These findings suggest that feedback from nonthermal energetic particles plays a crucial role in magnetic reconnection and particle acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

The DREAMS Project: Disentangling the Impact of Halo-to-halo Variance and Baryonic Feedback on Milky Way Dark Matter Density Profiles

In this work, we utilize a new suite of Milky Way–mass halos from the DREAMS Project, simulated with cold dark matter (CDM), to quantify the influence of baryon feedback and intrinsic halo-to-halo variance on dark matter density profiles. Our suite of 1024 halos varies over supernova and black hole feedback parameters from the IllustrisTNG model, as well as variations in two cosmological parameters. We find that, for the DREAMS parameter variations, Milky Way–mass dark matter density profiles in the IllustrisTNG model are largely insensitive to astrophysics and cosmology variations, with the dominant source of scatter instead arising from halo-to-halo variance. However, most of the (comparatively minor) feedback-driven variations come from the changes to supernova prescriptions. By comparing to dark-matter-only simulations, we find that the strongest supernova wind energies are so effective at preventing galaxy formation that the halos are nearly entirely collisionless dark matter. Finally, regardless of physics variation, all of the DREAMS halos are roughly consistent with a halo contracting adiabatically from the presence of baryons, unlike models that have bursty stellar feedback. This work represents a step toward assessing the uncertainty in Milky Way dark matter profiles, with direct implications for dark matter searches where systematic uncertainty in the density profile remains a major challenge.

Garcia, Alex M. [University of Virginia, Charlotte↗

DOE OSTI2026

Meteorological drivers of the low-cloud radiative feedback pattern effect and its uncertainty

The radiative feedback pattern effect remains a large source of uncertainty for both projections of future trends and interpretations of past trends in global temperature. The pattern effect is defined as the difference in feedbacks between transient and long-term simulations, and past work shows that is primarily attributed to changes in the marine low-cloud radiative feedback. Here we use low cloud meteorological kernels to map out both the primary cloud controlling factors through which changing surface temperature patterns drive changes in low-cloud feedback, as well as the sources of model spread. We find that the pattern effect is almost entirely driven by changes in estimated inversion strength (EIS) in the Southern Hemisphere, particularly in the South East Pacific and Southern Ocean. In both past and future simulations, inter-model spread is primarily caused by model differences in the sensitivity of low clouds to the environmental conditions, rather than differences in the simulated evolution of environmental conditions.

58 GEOSCIENCES↗

DOE OSTI2024

Relationship Between Tropical Cloud Feedback and Climatological Bias in Clouds

Abstract Global climate model (GCM) projections of future climate are uncertain largely due to a persistent spread in cloud feedback. This is despite efforts to reduce this model uncertainty through a variety of emergent constraints (ECs); with several studies suggesting an important role for present‐day biases in clouds. Here, we use three generations of GCMs to assess the value of climatological cloud metrics for constraining uncertainty in cloud feedback. We find that shortwave cloud radiative properties across the Southern Hemisphere extratropics are most robustly correlated with tropical cloud feedback (TCF). Using this relationship in conjunction with observations, we produce an EC that yields a TCF value of 0.52 ± 0.34 W/m 2 /K, which equates to a 34% reduction in uncertainty. Thus, we show that climatological cloud properties can be used to reduce uncertainty in how clouds will respond to future warming.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Prevention of resistive wall tearing mode major disruptions with feedback

Resistive wall tearing modes (RWTMs) can cause major disruptions. A signature of RWTMs is that the rational surface is sufficiently close to the wall to interact with it. For (m,n) = (2,1) modes, a RWTM requires normalized minor radius of the rational surface ρ q2 ≥ 0.75, which can also be expressed as q 75 ≤ 2. Major disruptions can occur when the criterion is satisfied. This is confirmed in simulations and theory and in a DIII-D locked mode disruption database. The q 75 < 2 criterion is valid at high β as well as at low β. A very important feature of RWTMs is that they can be feedback stabilized. If the ρ q2 criterion is not satisfied, or if the wall is ideally conducting, then the mode does not produce a major disruption, although it can produce a minor disruption. Feedback, or rotation of the mode at the wall by complex feedback, can emulate an ideal wall, preventing major disruptions. The ρ q2 criterion depends weakly on the wall radius. A simple geometric model of its dependence on wall radius is given.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones

Constraining cloud feedback in global climate models (GCMs) using observations is important for establishing accurate predictions of future climate. Uncertainty in shortwave cloud feedback (SW FB ) dominates uncertainty in total cloud feedback. Recent studies show a shift toward more positive extratropical SW FB in the latest generations of GCMs leading to the emergence of very high equilibrium climate sensitivity (ECS). In this study, we use precipitation efficiency and albedo susceptibility to constrain liquid water path (LWP) response to warming and SW FB in the Southern Ocean (SO; 50°–80°S). We analyze precipitation in extratropical cyclones (ECs) to learn about extratropical condensed water sink processes, combined with observations of clouds and moisture convergence, and use the analysis to better understand and constrain SW FB . We utilize a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model, version 6 (CAM6), to provide a constraint on SW FB based on observations from Clouds and the Earth’s Radiant Energy System (CERES) and Multisensor Advanced Climatology of LWP (MAC-LWP). We apply Gaussian process regression to emulate the model response to all parameters perturbed in the PPE. Confronting the emulator output with observations provides a new estimated response of Earth to global warming. Furthermore, our new estimates of SO LWP reduce the PPE range by 66%–72%, which results in a shortwave cloud radiative effect estimated range that is 27%–34% less than the PPE range. Observations suggest a more positive SO SW FB than the Community Earth System Model, version 2 (CESM2), and consequently do not reject the high climate sensitivity GCMs emerging from the Coupled Model Intercomparison Project phase 6 (CMIP6).

Atmosphere↗

DOE OSTI2024

Soil Moisture‐Cloud‐Precipitation Feedback in the Lower Atmosphere From Functional Decomposition of Satellite Observations

Abstract The feedback of topsoil moisture (SM) content on convective clouds and precipitation is not well understood and represented in the current generation of weather and climate models. Here, we use functional decomposition of satellite‐derived SM and cloud vertical profiles (CVP) to quantify the relationship between SM and the vertical distribution of cloud water in the central US. High‐dimensional model representation is used to disentangle the contributions of SM and other land‐surface and atmospheric variables to the CVP. Results show that the sign and strength of the SM‐cloud‐precipitation feedback varies with cloud height and time lag and displays a large spatial variability. Positive anomalies in antecedent 7‐hr SM and land‐surface temperature enhance cloud reflectivity up to 4 dBZ in the lower atmosphere about 1–3 km above the surface. Our approach presents new insights into the SM‐cloud‐precipitation feedback and aids in the diagnosis of land‐atmosphere interactions simulated by weather and climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

The Role of Land‐Atmosphere Feedbacks in Midlatitude Wintertime Surface Temperature Variability

Accurately representing synoptic near-surface temperature variability is crucial to predict weather extremes, yet models remain biased. Existing studies primarily attribute wintertime midlatitude near-surface temperature variability to tropospheric large-scale advection, assuming minimal land influence. However, nudging the model's circulation toward observations yields little improvement in wintertime temperature variance over Northern Hemisphere land, suggesting that land-atmosphere interactions also warrant attention. We introduce a new scaling framework for temperature variance that incorporates local land-atmosphere feedbacks. Comparing our framework to the mixing length approach—which links temperature variance to the meridional temperature gradient and air parcel displacement (mixing length)—shows that land-atmosphere feedbacks are inherently embedded in the mixing length, a connection previously overlooked. Roles of land–atmosphere feedbacks are evaluated via model experiments with perturbed circulation, land, or both. We find that longwave radiative damping dominates temperature variance responses over meridional temperature gradient when both land and circulation are perturbed.

atmosheric science↗

DOE OSTI2026

Pore-Scale Study on the Positive Feedback Between Stress and Porosity Caused by Pressure Solution in Porous Media

Pressure solution is an important process in the evolution of sedimentary rocks, which provide storage space for most of our petroleum resources. It directly influences the generation, migration, and storage of petroleum fluids in subsurface sedimentary rocks. Here, in this paper, we develop a pore-scale, mechanochemical model to demonstrate a possible positive feedback between the local porosity and pore surface stress, in which a higher local porosity causes a higher local pore surface stress, thus enhancing pressure solution and consequently further increasing the local porosity. Pore surface stress represents stress on a solid grain adjacent to a pore. Specifically, the pore-scale, mechanochemical model directly simulates the stress distribution over solid and pore surfaces using a finite element model. The dissolution of solids at the solid-pore interfaces under a far-from-equilibrium condition is simulated using a first-order kinetics model that accounts for the local stress distribution. The updated pore geometry, caused by pore surface dissolution, is then used in the stress simulation in the next numerical iteration. Two types of porous media, the Oriskany sandstone and an artificial porous medium with spherical pores, were tested in the mechanochemical simulation. The positive stress-porosity feedback during pressure solution was observed in both samples. In addition, the model quantitatively illustrated the distribution of local mineral dissolution rates on all pore surfaces, as well as its relation to the effective mineral dissolution rate of the entire sample. Based on the comparison between the two porous media, the local mineral dissolution was regulated by pore space distribution, geometry, and coalescence during pressure solution. This work is the first that uses direct, pore-scale numerical simulation to demonstrate the positive stress-porosity feedback during pressure solution, which has the potential to advance the understanding of the mechanical-chemical (MC) coupling in many geological processes that are relevant to subsurface energy systems, such as the recovery of petroleum hydrocarbons and geothermal energy.

CT scanning↗

DOE OSTI2025

Validation of Numerical Tools for Calculating Reactivity Feedback in Sodium Fast Reactors Using SEFOR Experimental Data

The Southwest Experimental Fast Oxide Reactor (SEFOR) was an experimental sodium-cooled fast breeder reactor operated from 1969 to 1972 with experiments designed to measure Doppler reactivity feedback in a wide temperature range from around 350 °F to temperatures approaching the melting point of mixed oxide fuel of around 5000 °F, providing valuable data for code validations. Co-supported by the Department of Energy (DOE) Fast Reactor Program (FRP) and the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the SEFOR benchmark project focused on using the experimental data to validate numerical tools that are used in industry and academia to design and license sodium-cooled fast reactors (SFRs). By the end of FY-25, substantial progress was achieved in the SEFOR benchmark study. A variety of numerical tools commonly used for modeling SFRs were applied to develop models for SEFOR core configurations I-D, I-E, I-I, and I-J. These included Monte Carlo codes such as MCNP, Serpent, and Shift; deterministic codes such as the legacy Argonne Reactor Computation (ARC) suite and the high-fidelity NEAMS code Griffin; and the system analysis code SAS4A/SASSYS-1 (SAS). Using these models, both SEFOR zero-power experiments and power-ascending tests were successfully simulated. Comparisons were performed against experimental measurements of core criticalities, reflector worth, kinetics parameters (Λ/βeff), isothermal reactivity feedback (from 350 °F to 760 °F at zero power), and power-ascending reactivity feedback (as power increased from 0.4 MW to 17 MW). In general, these comparisons demonstrated very good agreement between numerical results and experimental data. In Fiscal Year 26 (FY-26), the SEFOR benchmark project will continue to address the modeling issues identified in FY-25. Effort will focus on the simulation of reactivity insertion transients in SEFOR core II using the ARC/SAS model. Future work will also focus on incorporating BISON into the SEFOR core modeling process to enable the first Multiphysics simulations of the isothermal tests based on the MOOSE framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Probing the Impact of Radio-mode Feedback on the Properties of the Cool Circumgalactic Medium

We explore the influence of radio-mode feedback on the properties of the cool circumgalactic medium (CGM). To this end, we assemble a statistical sample of approximately 30,000 radio galaxies with background quasars by combining optical spectroscopic measurements of luminous red galaxies and quasars from the year 1 data set of the Dark Energy Spectroscopic Instrument and radio sources from the LOw-Frequency ARray Two-metre Sky Survey (LoTSS) DR2 catalog and the Very Large Array Sky Survey (VLASS) quick-look catalog. Galaxies with similar optical properties but with no radio counterparts in LoTSS and VLASS are selected as the control group. We measure the cool CGM properties of radio galaxies and their control samples traced by Mg ii absorption lines, including covering fraction, rest equivalent width, and gas kinematics. Our results show no significant difference in the properties of gas around radio galaxies and their control sample, indicating that the operating radio-mode feedback of massive galaxies does not produce detectable effects on the properties of the cool CGM. Finally, we show that the CGM of radio galaxies contains a nonnegligible amount of cool gas with approximately 10 10 M ⊙ . This abundance can place a stringent constraint on the radio-mode feedback models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Comparing XRISM Cluster Velocity Dispersions with Predictions from Cosmological Simulations: Are Feedback Models Too Ejective?

The dynamics of the intracluster medium (ICM), the hot plasma that fills galaxy clusters, are shaped by gravity-driven cluster mergers and feedback from supermassive black holes (SMBHs) in the cluster cores. XRISM measurements of ICM velocities in several clusters offer insights into these processes. We compare XRISM measurements for nine galaxy clusters (Virgo, Perseus, Centaurus, Hydra-A, PKS 0745–19, A2029, Coma, A2319, and Ophiuchus) with predictions from three state-of-the-art cosmological simulation suites, TNG-Cluster, the Three Hundred Project GADGET-X, and GIZMO-SIMBA, that employ different models of feedback. In cool cores, XRISM reveals systematically lower velocity dispersions than the simulations predict, with all 10 measurements below the median simulated values by a factor of 1.5–1.7 on average and all falling within the bottom 10% of the predicted distributions. The observed kinetic-to-total pressure ratio is also lower, with a median value of 2.2%, compared to the predicted 5.0%–6.5% for the three simulations. Outside the cool cores and in non-cool-core (NCC) clusters, simulations show better agreement with XRISM measurements, except for the outskirts of the relaxed, cool-core cluster A2029, which exhibits an exceptionally low kinetic pressure support (<1%), with none of the simulated systems in either of the three suites reaching such low levels. The NCC Coma and A2319 exhibit dispersions at the lower end but within the simulated spread. Our comparison suggests that the three numerical models may overestimate the kinetic effects of SMBH feedback in cluster cores. Additional XRISM observations of NCC clusters will clarify if there is a systematic tension in the gravity-dominated regime as well.

galaxy clusters↗