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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Functional equations and separation of variables for exact g -function

The g-function is a measure of degrees of freedom associated to a boundary of two-dimensional quantum field theories. In integrable theories, it can be computed exactly in a form of the Fredholm determinant, but it is often hard to evaluate numerically. In this paper, we derive functional equations — or equivalently integral equations of the thermodynamic Bethe ansatz (TBA) type — which directly compute the g-function in the simplest integrable theory; the sinh-Gordon theory at the self-dual point. The derivation is based on the classic result by Tracy and Widom on the relation between Fredholm determinants and TBA, which was used also in the context of topological string. We demonstrate the efficiency of our formulation through the numerical computation and compare the results in the UV limit with the Liouville CFT. As a side result, we present multiple integrals of Q-functions which we conjecture to describe a universal part of the g-function, and discuss its implication to integrable spin chains.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The connection between nonzero density and spontaneous symmetry breaking for interacting scalars

We consider U(1)-symmetric scalar quantum field theories at zero temperature. At nonzero charge densities, the ground state of these systems is usually assumed to be a superfluid phase, in which the global symmetry is spontaneously broken along with Lorentz boosts and time translations. We show that, in d > 2 spacetime dimensions, this expectation is always realized at one loop for arbitrary non-derivative interactions, confirming that the physically distinct phenomena of nonzero charge density and spontaneous symmetry breaking occur simultaneously in these systems. We quantify this result by deriving universal scaling relations for the symmetry breaking scale as a function of the charge density, at low and high density. Moreover, we show that the critical value of μ above which a nonzero density develops coincides with the pole mass in the unbroken, Poincaré invariant vacuum of the theory. The same conclusions hold non-perturbatively for an O(N) theory with quartic interactions in d = 3 and 4, at leading order in the 1/N expansion. We derive these results by computing analytically the zero-temperature, finite-μ one-loop effective potential, paying special attention to subtle points related to the iε terms. We check our results against the one-loop low-energy effective action for the superfluid phonons in λΦ 4 theory in d = 4 previously derived by Joyce and ourselves, which we further generalize to arbitrary potential interactions and arbitrary dimensions. As a byproduct, we find analytically the one-loop scaling dimension of the lightest charge-n operator for the λΦ 6 conformal superfluid in d = 3, at leading order in 1/n, reproducing a numerical result of Badel et al. For a λΦ 4 superfluid in d = 4, we also reproduce the Lee-Huang-Yang relation and compute relativistic corrections to it. Finally, we discuss possible extensions of our results beyond perturbation theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Time-series forecasting using manifold learning, radial basis function interpolation, and geometric harmonics

We address a three-tier numerical framework based on nonlinear manifold learning for the forecasting of high-dimensional time series, relaxing the “curse of dimensionality” related to the training phase of surrogate/machine learning models. At the first step, we embed the high-dimensional time series into a reduced low-dimensional space using nonlinear manifold learning (local linear embedding and parsimonious diffusion maps). Then, we construct reduced-order surrogate models on the manifold (here, for our illustrations, we used multivariate autoregressive and Gaussian process regression models) to forecast the embedded dynamics. Finally, we solve the pre-image problem, thus lifting the embedded time series back to the original high-dimensional space using radial basis function interpolation and geometric harmonics. The proposed numerical data-driven scheme can also be applied as a reduced-order model procedure for the numerical solution/propagation of the (transient) dynamics of partial differential equations (PDEs). In conclusion, we assess the performance of the proposed scheme via three different families of problems: (a) the forecasting of synthetic time series generated by three simplistic linear and weakly nonlinear stochastic models resembling electroencephalography signals, (b) the prediction/propagation of the solution profiles of a linear parabolic PDE and the Brusselator model (a set of two nonlinear parabolic PDEs), and (c) the forecasting of a real-world data set containing daily time series of ten key foreign exchange rates spanning the time period 3 September 2001–29 October 2020.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Compressive strength improvements from noncircular carbon fibers: A numerical study

The benefits of high-performance unidirectional carbon fiber composites are limited in many cost-driven industries due to the high cost relative to alternative reinforcement fibers. Low-cost carbon fibers have been previously proposed, but the longitudinal compressive strength continues to be a limiting factor or studies are based on simplifications that warrant further analysis. A micromechanical model is used to (1) determine if the longitudinal compressive strength of composites can be improved with noncircular carbon fiber shapes and (2) characterize why some shapes are stronger than others in compression. In comparison to circular fibers, the results suggest that the strength can be increased by 10%–13% by using a specific six-lobe fiber shape and by 6%–9% for a three-lobe fiber shape. A slight increase is predicted in the compressive strength of the study two-lobe fiber but has the highest uncertainty and sensitivity to fiber orientation and misalignment direction. The underlying mechanism governing the compressive failure of the composites was linked to the unique stress fields created by the lobes, particularly the pressure stress in the matrix. Importantly, this work provides mechanics-based evidence of strength improvements from noncircular fiber shapes and insight on how matrix yielding is altered with alternative fiber shapes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Extreme radiation emission regime for electron beams in strong focusing ion channels and undulators

A fundamental comparison between a magnetic undulator and an ion channel, or betatron, radiation from relativistic electrons is presented. While conventional theories nominally range from the undulator (𝐾 <1) to the wiggler (𝐾 >1) regime, they are only applicable for sufficiently large Lorentz factors (𝛾 0 ≫𝐾). They therefore do not account for high 𝐾/𝛾 0 cases, for which we show that particle trajectories and radiation characteristics strongly deviate from the linear predictions in both magnetic undulators and ion channels. This problem arises from the fundamental differences between a magnetostatically and electrostatically induced oscillation. A reformulation of both the ion channel betatron wavelength and amplitude, as well as the same parameters in a magnetic undulator, permits us to compare cases with equivalent oscillation period and amplitude in the two different scenarios. The notable differences in spectral features of the two radiation mechanisms can then be addressed via numerical simulations of single particle as well as full beam dynamics. Additionally, we identify and quantify a novel transverse orbit precession effect in ion channels for particles with initial angular momentum relative to the device axis. This effect, which is significant in cases of strong transverse kinetic energy oscillations, alters both the radiation divergence and the beam emittance. In this paper, we present this new theoretical framework and compare its results with numerical simulation applied to realizable experimental tests of such radiation sources.

Frazzitta, Andrea [University of Rome “La Sapienza↗
DOE OSTI2024

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

MOSCATO Development and Integration in Fiscal Year 2025: Implementation of Multiphase, Multiphysics Modeling Capabilities for Molten Salt Systems

MOSCATO (Molten Salt Chemistry and Transport) is a multiphysics code that provides high-fidelity, coupled simulations of fluid flow, heat transfer, mass transfer, chemistry, electrochemical phenomena, and alloy corrosion for molten salt systems. In FY25, significant developments were made to the code package, enhancing its capabilities for modeling all relevant phenomena within operating moltens salt reactors (MSRs). The developments and activities in FY25 included: 1. Implementation of Level-Set methods to enable modeling of single-bubble behavior in molten salts. In FY25, the Level-Set two-phase flow modeling implementation was improved to simulate single bubble behavior with molten salt media. The large density and viscosity ratios between typical gases and molten salt liquids present challenges for these types of numerical solvers. With enhancements to the pressure projection method, MOSCATO’s Level-Set solver was able to be successfully validated to experiments related to helium bubble rise in stagnant molten salt. The simulated bubble rising velocity showed reasonable good agreement with experimental measurements. The bubble shape and dynamics were also visually compared with experimental snapshots, demonstrating a good qualitative match. 2. Generation of mass transfer correlations for multiphase flow systems. To enable calculations of the tritium transport across the interface between gas bubbles and salt, we modeled high- Schmidt-number mass transfer around a sphere across a broad range of Reynolds numbers. The mesh near the sphere surface was highly refined to resolve steep concentration gradients caused by the low diffusion coefficient. Literature-based mass transfer correlations were compared with the numerical results, and modifications were proposed to improve agreement, particularly at higher Schmidt numbers. These mass transfer correlations were subsequently provided to other national laboratories to help enable high quality mass transfer simulations using lower-order solvers under development within the NEAMS program. 3. Preliminary implementation of a bubbly flow solver. To model bubbly flow in molten salt, we implemented a bubbly flow solver for void fractions less than 5%. To do so, an algebraic relative velocity model that assumes small bubbles with rapid momentum equilibration was added to MOSCATO to compute bubble velocities. Preliminary comparisons with experimental data showed reasonable agreement, and further improvements are underway. 4. Generation of mass transfer correlations for MSRE subchannel The Molten-Salt Reactor Experiment (MSRE) was a landmark historical project that demonstrated the feasibility of molten-salt reactor technology. The MSRE campaign also generated a significant body of experimental data and reports that continue to support molten-salt–related research. In this report, the MSRE core subchannel was used as the reference geometry for a mass transfer study performed with MOSCATO. The geometry and computational mesh were adapted from a previous study, providing adequate resolution for the relatively low Reynolds number in this case. Additional mesh refinement was applied to reach higher Schmidt numbers, enabling the derivation of a reliable mass-transfer correlation for the present scenario. 5. Simulations of oxygen ingressions into molten salt. In the previous fiscal year, we initiated a study to simulate oxygen ingression in stagnant salt. As oxygen enters the salt through its surface, it reacts with Ce 3+ to form solid CeO 2 and other reaction products. To more fully capture the complex diffusion-convection-reaction mechanisms, capabilities for modeling natural convection in the salt vessel were added. These were needed as the flow of the ingressed gas induced flow in the salt caused by surface shear and non-isothermal effects. With these updated physics in place, we were able to successfully reproduce the experimental results for the rate of change of CeCl 3 concentrations versus time. 6. Flow corrosion model validation. In FY24, MOSCATO’s corrosion model was validated against static corrosion experiments. In FY25, this work was extended to a flow corrosion experiment, where FLiNaK salt was driven by natural convection, with initial salt impurities to initiate corrosion. Despite uncertainties in parameters such as elemental diffusion coefficients in the alloy and unknown H + concentrations, the simulations achieved good agreement with experimental results, especially in predicting sample mass losses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Tunable Metamaterials for Impact Mitigation

Traditional methods of shielding fragile goods and human tissues from impact energy rely on isotropic foam materials. The mechanical properties of these foams are inferior to an emerging class of metamaterials called plate lattices, which have predominantly been fabricated in simple 2.5-dimensional geometries using conventional methods that constrain the feasible design space. Here in this work, additive manufacturing is used to relax these constraints and realize plate lattice metamaterials with nontrivial, locally varying geometry. The limitations of traditional computer-aided design tools are circumvented and allow the simulation of complex buckling and collapse behaviors without a manual meshing step. By validating these simulations against experimental data from tests on fabricated samples, sweeping exploration of the plate lattice design space is enabled. Numerical and experimental tests demonstrate plate lattices absorb up to six times more impact energy at equivalent densities relative to foams and shield objects from impacts ten times more energetic while transmitting equivalent peak stresses. In contrast to previous investigations of plate lattice metamaterials, designs with nonuniform geometric prebuckling in the out-of-plane direction is explored and showed that these designs exhibit 10% higher energy absorption efficiency on average and 25% higher in the highest-performing design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Flowback Test Analyses at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) Site

Abstract In 2017 and 2019, injection testing was carried out in three zones in a vertical well in granite at the Frontier Observatory for Research in Geothermal Energy site near Milford, Utah, USA. In several injection cycles, flowback was implemented rather than shut-in. The goal was to explore an alternative to prolonged shut-in periods for inferring closure stress, formation compressibility, and formation permeability (permeability thickness product). The flowback procedures involved a cyclic flowback/shut-in, while pressure decreased. The flowback data are presented, and analyses are shown. The inferred closure stress(es) from flowback analyses are lower than for equivalent injection cycles that were strictly shut-in. Relatively high formation compressibility obtained from the flowback analyses indicates an extensive, fractured system. This study also includes numerical simulation of the flowback events. The numerical model shows that the rebound pressure is not necessarily the lower bound of the minimum principal stress. The signature of stiffness change can be identified as the process when the depletion mainly transitions from hydraulic fracture to natural fractures from numerical analysis. Overall, flowback potentially has advantages over shut-in because of the reduced time to closure.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Energy sector portfolio analysis with uncertainty

Governments are dealing with the challenge of how to efficiently invest in research and development portfolios related to energy technologies. Research and development investment decisions in the energy space are especially difficult due to numerous risks and uncertainties, and due to the complexity of energy's interactions with the broad economy. Historically, much of the U.S. Department of Energy's in-depth research and development analyses focused on assessing the impact of a research and development activity in isolation from other available opportunities and did not substantially consider risk and uncertainty. Endeavoring to combine integrated energy-economy modeling with uncertainty analysis and technology-specific research and development activities, the U.S. Department of Energy commissioned the development of the Stochastic Energy Deployment System to support and improve public energy research and development decision-making. The Stochastic Energy Deployment System draws from expert-elicited probability distributions for research and development-driven improvements in technology cost and performance, and it uses Monte Carlo simulations to evaluate the likelihood of outcomes within a system dynamics energy-economy model. The framework estimates the uncertain benefits and costs of various research and development portfolios and provides insight into the probability of meeting national technology goals, while accounting for interactions with the larger economy and for interactions among research and development investments spanning many energy sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Systems biology-guided understanding of white-rot fungi for biotechnological applications: A review

Plant-derived biomass is the most abundant biogenic carbon source on Earth. Despite this, only a small clade of organisms known as white-rot fungi (WRF) can efficiently break down both the polysaccharide and lignin components of plant cell walls. This unique ability imparts a key role for WRF in global carbon cycling and highlights their potential utilization in diverse biotechnological applications. To date, research on WRF has primarily focused on their extracellular 'digestive enzymes', while knowledge of their intracellular metabolism remains underexplored. Systems biology has been demonstrated to be a powerful approach to elucidate biological processes in numerous organisms, including WRF. Thus, here we review systems biology methods applied to WRF to date, highlight observations related to their intracellular metabolism, and conduct a comparative extracellular proteomic analysis to establish further correlations between WRF species, enzymes, and cultivation conditions. Lastly, we discuss biotechnological opportunities of WRF as well as challenges and future research directions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effects of particle shape and surface roughness on van der Waals interactions and coupling to dynamics in nanocrystals

The van der Waals interaction between colloids and nanoparticles is one of the key components to understanding particle aggregation, attachment, and assembly. While the ubiquity of anisotropic particle shapes and surface roughness is well-recognized in nanocrystalline materials, the effect of both on van der Waals forces and torques has not been adequately investigated. Here, in this study, we develop a numerical scheme and determine the van der Waals forces and torques between cubic particles with multiple configurations and relative orientations. Our results show that the van der Waals torque due to anisotropic particle shapes is appreciable at nearly all configurations and mutual angles, outcompeting Brownian motion for various materials systems and conditions. The effect of surface roughness increases this shape effect, resulting in stronger van der Waals interactions ascribed to protrusions in the rough surfaces. Moreover, a scaling analysis indicates that the surface roughness alters the separation dependence of the van der Waals force and, more importantly, significantly influences the dynamics of two approaching particles. Our results clearly demonstrate that surface roughness and anisotropic shape play a crucial role in the energetics and kinetics of various particle-scale and emergent phenomena, such as crystal growth by oriented attachment, nanomaterials synthesis and assembly, mud flow rheology, as well as the deposition of natural nanocrystals within the subsurface.

Arbitrary configurations↗
DOE OSTI2025

Accelerating magnonic simulations with the pseudospectral Landau-Lifshitz equation

The pseudospectral Landau-Lifshitz (PS-LL) model can describe atomic-scale magnetic exchange interactions within a continuum framework. This is achieved by employing a convolution kernel that models the nonlocal interaction in a grid-independent manner. Even though the PS-LL was originally introduced to address atomic exchange, any nonlocal kernel can be modeled. In the field of magnonics, the dipole field is fundamental to describe the dispersion relation of magnons, the quasiparticle representation of angular momentum. Because dipole-dipole interactions are long-range, numerical approaches typically rely on convolutions. Here, we demonstrate that the PS-LL model can be used to perform magnonic simulations with a single convolution kernel derived from analytical solutions. We demonstrate a twofold increase in computational speed compared with the full dipole calculation. This approach is valid insofar as the excitations are linear, which is typically the case for magnons. Our results have the potential to accelerate magnonic research, particularly for the inverse design method, where several simulations must be performed to achieve the desired outcome.

Mathematics and computing↗
DOE OSTI2022

Bosonic field digitization for quantum computers

Quantum simulation of quantum field theory is a flagship application of quantum computers that promises to deliver capabilities beyond classical computing. The realization of quantum advantage will require methods that can accurately predict error scaling as a function of the resolution and parameters of the model and that can be implemented efficiently on quantum hardware. In this paper, we address the representation of lattice bosonic fields in a discretized field amplitude basis, develop methods to predict error scaling, and present efficient qubit implementation strategies. A low-energy subspace of the bosonic Hilbert space, defined by a boson occupation number cutoff, can be represented with exponentially good accuracy by a low-energy subspace of a finite-size Hilbert space. The finite representation construction and the associated errors are directly related to the accuracy of the Nyquist-Shannon sampling and the finite Fourier transforms of the boson number states in the field and the conjugate-field bases. We analyze the relation between the boson mass, the discretization parameters used for wave function sampling, and the finite representation size. Numerical simulations of small size Φ 4 problems demonstrate that the boson mass optimizing the sampling of the ground state wave function is a good approximation to the optimal boson mass yielding the minimum low-energy subspace size. However, we find that accurate sampling of general wave functions does not necessarily result in accurate representation. Finally, we develop methods for validating and adjusting the discretization parameters to achieve more accurate simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Effective interactions between nuclear clusters

In this work, the effective interactions between two nuclear clusters, d + d, t + t, and α + α, are investigated within a cluster model using local nucleon-nucleon (NN) forces. It is shown that the interaction in the spin-aligned d + d system is repulsive for all intercluster distances, whereas the α + α and spin-aligned t + t systems are attractive at intermediate distances. The Pauli blocking between identical-nucleon pairs is responsible for the cluster-cluster repulsion and becomes dominant in the shallow binding limit. We demonstrate that two d clusters could be bound if the NN force has nonzero range and is strong enough to form a deeply bound d cluster, or if the NN force has both even-parity and odd-parity attraction. Effective dimer-dimer interactions for general quantum systems of two-component fermions are also discussed in heavy-light mass limit, where one component is much heavier than the other, and their relation to intercluster interactions in nuclear systems are discussed. Our findings provide a conceptual foundation for conclusions obtained numerically in the literature, that increasing the range or strength of the local part of the attractive nucleon-nucleon interaction results in a more attractive cluster-cluster interaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) (Field Campaign Report)

The Arctic is rapidly changing, and these changes have substantial societal relevance. First, arctic change is a leading sign of global change, as the warming observed in the Arctic is 2-3 times faster than observed across the rest of the globe. This so-called arctic amplification is due to numerous feedbacks, including those linked to the declining sea ice. Broad arctic changes are also hypothesized to be related to shifts in large-scale circulation patterns that may have implications for mid-latitude weather and ocean circulation. Arctic change is further affecting the oceans through acidification that threatens food supplies. Declining sea ice also opens the Arctic for new resource development, shipping routes, tourism, and other commercial activities. Lastly, the changing Arctic is a hotbed for geopolitical challenges as nations vie for influence and control of this resource-rich and newly accessible region. Clearly the Arctic and its changes are playing a huge role in our Earth both from a geophysical and socio-political standpoint. To navigate, manage, and respond to the challenges associated with arctic change requires a vastly improved understanding of the coupled arctic system, and the drivers and implications of these changes. It is essential to better understand the physical basis for why the arctic sea ice is declining, the associated feedbacks that work to amplify or modulate this decline, and the myriad ways that the Earth system is responding. As a result of these changes and uncertainties, there are increasing societal needs for improved model predictive skill in the Arctic, to address pressing gaps in global climate prediction, to advance forecast skills for regional and hemispheric weather and sea ice, and to ensure robust ecosystem models that realistically link physical and biological systems. To fulfill these core needs requires new, sophisticated, and cross-cutting observations within the rapidly changing arctic ice pack.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Turbulent Stress Spectrum in the Inertial and Subinertial Ranges

For velocity and magnetic fields, the turbulent pressure and, more generally, the squared fields such as the components of the turbulent stress tensor, play important roles in astrophysics. For both one and three dimensions, we derive the equations relating the energy spectra of the fields to the spectra of their squares. We solve the resulting integrals numerically and show that for turbulent energy spectra of Kolmogorov type, the spectral slope of the stress spectrum is also of Kolmogorov type. For shallower turbulence spectra, the slope of the stress spectrum quickly approaches that of white noise, regardless of how blue the spectrum of the field is. For fully helical fields, the stress spectrum is elevated by about a factor of two in the subinertial range, while that in the inertial range remains unchanged. We discuss possible implications for understanding the spectrum of primordial gravitational waves from causally generated magnetic fields during cosmological phase transitions in the early universe. We also discuss potential diagnostic applications to the interstellar medium, where polarization and scintillation measurements characterize the square of the magnetic field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Parametric Study of the SASI Comparing General Relativistic and Nonrelativistic Treatments

We present numerical results from a parameter study of the standing accretion shock instability (SASI), investigating the impact of general relativity (GR) on the dynamics. Using GR hydrodynamics with GR gravity, and nonrelativistic (NR) hydrodynamics with Newtonian gravity, in an idealized model setting, we vary the initial radius of the shock, and by varying its mass and radius in concert, the proto-neutron star compactness. We investigate four compactnesses expected in a post-bounce core-collapse supernova (CCSN). We find that GR leads to a longer SASI oscillation period, with ratios between the GR and NR cases as large as 1.29 for the highest-compactness suite. We also find that GR leads to a slower SASI growth rate, with ratios between the GR and NR cases as low as 0.47 for the highest-compactness suite. We discuss implications of our results for CCSN simulations.

79 ASTRONOMY AND ASTROPHYSICS↗