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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Possible Spin-Triplet Excitonic Insulator in the Ultraquantum Limit of HfTe 5

More than 50 years ago, excitonic insulators formed by the pairing of electrons and holes due to Coulomb interactions were first predicted [A. N. Kozlov and L. A. Maksimov, Sov. J. Exp. Theor. Phys. 21, 790 (1965); L. V. Keldysh and Y. V. Kopaev, Sov. Phys. Solid State 6, 2219 (1965); D. Jérome, T. M. Rice, and W. Kohn, Phys. Rev. 158, 462 (1967)]. Since then, excitonic insulators have been observed in various classes of materials, including quantum Hall bilayers, graphite, transition metal chalcogenides, and more recently in moiré superlattices. In these excitonic insulators, an electron and a hole with the same spin bind together, and the resulting exciton is a spin singlet. Here, we report the experimental observation of a spin-triplet excitonic insulator in the ultra-quantum limit of a three-dimensional topological material HfTe 5 . We observe that the spin-polarized zeroth Landau bands dispersing along the field direction cross each other beyond a characteristic magnetic field in HfTe 5 , forming the one-dimensional Weyl mode. Transport measurements reveal the emergence of a gap of about 2⁢5⁢0 μ⁢eV when the field surpasses a critical threshold. By performing the material-specific modeling, we identify this gap as a consequence of a spin-triplet exciton formation, where electrons and holes with opposite spin form bound states, and the translational symmetry is preserved. The system reaches charge neutrality following the gap opening, as evidenced by the zero Hall conductivity over a wide magnetic field range (10–72 T). In conclusion, our finding of the spin-triplet excitonic insulator paves the way for studying novel spin transport including spin superfluidity, spin Josephson currents, and Coulomb drag of spin currents in analogy to the transport properties associated with the layer pseudospin in quantum Hall bilayers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ultrafast Excitonic Response in Two-Dimensional Hybrid Perovskites Driven by Intense Midinfrared Pulses

Two-dimensional organic-inorganic hybrid perovskites (2DHPs) are natural quantum-well-like materials, in which strong quantum and dielectric confinement effects due to the organic spacers give rise to tightly bound excitons with large binding energy. To examine the mutual interactions between the organic spacer cations and the inorganic charge-residing octahedral framework in 2DHPs, here we perform femtosecond pump-probe spectroscopy by direct vibrational pumping of the organic spacers, followed by a visible-to-ultraviolet probe covering their excitonic resonances. Measurements on prototypical lead-bromide based 2DHP compounds, (BA) 2 ⁢PbBr 4 and (BA) 2 ⁢(FA)⁢Pb 2 ⁢Br 7 (BA+ = butylammonium; FA + = formamidinium), reveal two distinct regimes of the temporal response. The first regime is dominated by a pump-induced transient expansion of the organic spacer layers that reduces the exciton oscillator strength, whereas the second regime arises from pump-induced lattice heating effects primarily associated with a spectral shift of the exciton energy. In addition, vibrational excitation enhances the biexciton emission, which we attribute to a stronger intralayer exciton confinement as well as vibrationally induced exciton detrapping from defect states. Finally, our study provides fundamental insights regarding the impact of organic spacers on excitons in 2DHPs, as well as the excited-state dynamics and vibrational energy dissipation in these structurally diverse materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Combined Normal and Disruption, Electromagnetic Transient, Thermal, and Structural Analysis of COMPASS Upgrade

We report that COMPASS Upgrade is a replacement for the COMPASS device at the Institute of Plasma Physics (IPP) of the Czech Academy of Sciences. It is a cryogenic copper machine with a major radius of 0.89 m, with 5 T at the plasma centerline and 2-MA plasma current. It is intended to develop ITER relevant plasma densities and high power fluxes in the divertor region. The entire vacuum vessel is planned to reach 500 °C. The COMPASS-U TF coil is a bitter plate-like design with radial conductor plates that extend the width of the TF inner leg. Currents redistribute radially based on resistive and inductive effects. This necessitates an electromagnetic (EM) transient analysis of the coil current distribution. For copper coils like COMPASS Upgrade, the solution must be coupled with a thermal solution to properly include the temperature-dependent resistive effects. The EM transient solution includes the TF magnetic loads, and a stress pass on the results produces in-plane loads. The EM solution chosen requires inclusion of all the conducting and nonconducting regions surrounding the TF coil. With the TF current distribution solved, the addition of the poloidal coils and resulting background fields allows the determination of the out-of-plane loads. Integration of the Joule heating produced from the EM solution produces temperature distributions throughout the shot, which can be read in to a structural pass to include thermal stresses in the evaluation. This is true of both TF and PF temperature prediction with appropriate packing fractions. Currents in the PF coils, with computed background fields, produce Lorentz loads. Time transients of the PF currents produce startup eddy currents in the structures included in the model; inclusion of the vessel and other passive structures allows these to be included in a stress pass. The EM transient solution includes all the elements needed for a disruption analysis with prescribed motions and quench of the plasma. From a model originally intended to simulate current diffusion in the TF coil, the analysis can be refined to be used to predict the performance of most of the components of the tokamak or provide boundary conditions for more detailed submodels. In this article, the use of the current diffusion model for bounding assessments of the COMPASS Upgrade TF, PF, vessel, external structure, and disruption analyses will be presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Shot-noise-induced lower temperature limit of the nonneutral plasma parallel temperature diagnostic

Abstract We develop a new algorithm to estimate the temperature of a nonneutral plasma in a Penning-Malmberg trap. The algorithm analyzes data obtained by slowly lowering a voltage that confines one end of the plasma and collecting escaping charges, and is a maximum likelihood estimator based on a physically-motivated model of the escape protocol presented in (Beck in Measurement of the magnetic and temperature dependence of the electron-electron anisotropic temperature relaxation rate. PhD thesis, 1990). Significantly, our algorithm may be used on single-count data, allowing for improved fits with low numbers of escaping electrons. This is important for low-temperature plasmas such as those used in antihydrogen trapping. We perform a Monte Carlo simulation of our algorithm, and assess its robustness to intrinsic shot noise and external noise. The assumptions in this paper allow for a lower bound for measurable plasma temperatures of approximately $3\,\mathrm{K}$ 3 K for plasmas of length $1\,\mathrm{cm}$ 1 cm , with approximately 100 particle counts needed for an accuracy of $\pm 10 \%$ ± 10 % .

Zhong, Adrianne (ORCID:0000000162618736)↗
DOE OSTI2020

waveSZ: A Hardware-Algorithm Co-Design of Efficient Lossy Compression for Scientific Data

Error-bounded lossy compression is critical to the success of extreme-scale scientific research because of ever-increasing volumes of data produced by today's high-performance computing (HPC) applications. Not only can error-controlled lossy compressors significantly reduce the I/O and storage burden but they can retain high data fidelity for post analysis. Existing state-of-the-art lossy compressors, however, generally suffer from relatively low compression and decompression throughput (up to hundreds of megabytes per second on a single CPU core), which considerably restrict the adoption of lossy compression by many HPC applications especially those with a fairly high data production rate. In this paper, we propose a highly efficient lossy compression approach based on field programmable gate arrays (FPGAs) under the state-of-the-art lossy compression model SZ. Our contributions are fourfold. (1) We adopt a wavefront memory layout to alleviate the data dependency during the prediction for higher-dimensional predictors, such as the Lorenzo predictor. (2) We propose a co-design framework named WAVESZ based on the wavefront memory layout and the characteristics of SZ algorithm and carefully implement it by using high-level synthesis. (3) We propose a hardware-algorithm co-optimization method to improve the performance. (4) We evaluate our proposed WAVESZ on three real-world HPC simulation datasets from the Scientific Data Reduction Benchmarks and compare it with other state-of-the-art methods on both CPUs and FPGAs. Experiments show that our WAVESZ can improve SZ's compression throughput by 6.9x similar to 8.7x over the production version running on a state-of-the-art CPU and improve the compression ratio and throughput by 2.1x and 5.8x on average, respectively, respectively, compared with the state-of-the-art FPGA design.

Compression Ratio↗
DOE OSTI2020

On Mixed-Integer Programming Formulations for the Unit Commitment Problem

We provide a comprehensive overview of mixed-integer programming formulations for the unit commitment (UC) problem. UC formulations have been an especially active area of research over the past 12 years due to their practical importance in power grid operations, and this paper serves as a capstone for this line of work. We additionally provide publicly available reference implementations of all formulations examined. We computationally test existing and novel UC formulations on a suite of instances drawn from both academic and real-world data sources. Driven by our computational experience from this and previous work, we contribute some additional formulations for both generator production upper bounds and piecewise linear production costs. By composing new UC formulations using existing components found in the literature and new components introduced in this paper, we demonstrate that performance can be significantly improved—and in the process, we identify a new state-of-the-art UC formulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Leveraging Cell Expansion Sensing in State of Charge Estimation: Practical Considerations

Measurements such as current and terminal voltage that are typically used to determine the battery’s state of charge (SOC) are augmented with measured force associated with electrode expansion as the lithium intercalates in its structure. The combination of the sensed behavior is shown to improve SOC estimation even for the lithium ion iron phosphate (LFP) chemistry, where the voltage–SOC relation is flat (low slope) making SOC estimation using measured voltage difficult. For the LFP cells, the measured force has a non-monotonic F–SOC relationship. This presents a challenge for estimation as multiple force values can correspond to the same SOC. The traditional linear quadratic estimator can be driven to an incorrect SOC value. To address these difficulties, a novel switching estimation gain is used based on determining the operating region that corresponds to the actual SOC. Moreover, a drift in the measured force associated with a shift of the cell SOC–expansion behavior over time is addressed with a bias estimator for the force signal. The performance of Voltage-based (V) and Voltage and Force-based (V&F) SOC estimation algorithms are then compared and evaluated against a desired ±5% absolute error bound of the SOC using a dynamic stress test current protocol that tests the proposed estimation scheme across wide range of SOC and current rates.

25 ENERGY STORAGE↗
DOE OSTI2023

Dimming the Lights: 2D Simulations of Deflagrations of Hybrid C/O/Ne White Dwarfs Using FLASH

The dimmest and most numerous outlier of the Type Ia supernova population, the Type Iax event, is increasingly being found in the results of observational campaigns. There is currently no single accepted model to describe these events. This 2D study explores the viability of modeling Type Iax events as a hybrid C/O/Ne white dwarf progenitor undergoing a deflagration using the multiphysics software FLASH. This hybrid was created using the stellar evolution code MESA, and its C-depleted core and mixed structure have demonstrated lower yields than traditional C/O progenitors in previous deflagration-to-detonation studies. To generate a sample, 30 “realizations” of this simulation were performed, the only difference being the shape of the initial match head used to start the deflagration. Consistent with earlier work, these realizations produce the familiar hot dense bound remnant surrounded by sparse ejecta. Our results indicate that the majority of the star remains unburned (∼70%) and bound (>90%). Our realizations produce total ejecta yields on the order of 10 −2 –10 −1 M ☉ , ejected 56 Ni yields on the order of 10 −4 –10 −2 M ☉ , and ejecta kinetic energies on the order of 10 48 –10 49 erg. Compared to yields inferred from recent observations of the dimmest Type Iax events—SN 2007qd, SN 2008ha, SN 2010ae, SN 2019gsc, SN 2019muj, SN 2020kyg, and SN 2021fcg—our simulation produces comparable 56 Ni yields but too-small total yields and kinetic energies. Reignition of the remnant is also seen in some realizations.

Hydrodynamical simulations↗
DOE OSTI2025

Dial

A key step in almost all scientific endeavors is answering the question: Given this data I already collected, what new data do I expect will yield the most useful information toward my scientific objective? The area of (sequential) experimental design has long been investigating answers to this question, but in recent years techniques from the machine learning subfield of active learning are increasingly applied. Researchers need a simple software tool for active learning applied to experimental design that can easily integrate into their existing workflows. This computer code, Dial, provides a microservice in ORNL's INTERSECT ecosystem for active learning applied to experimental design. By being part of the INTERSECT ecosystem, Dial is simple to integrate into any INTERSECT-based workflow. Dial provides multiple backend options, where a backend is an implementation of a specific active learning method. Users can select the backend that performs best for their application. Developers can also add new backends as needed. At its core, Dial receives a set of pre-existing measurements and input parameter bounds and then recommends one or more new sets of parameters to measure. Dial also includes interfaces to other microservices in the INTERSECT ecosystem so that it can be incorporated into INTERSECT campaigns. Dial provides a simple, yet powerful interface to convert automated INTERSECT workflows into autonomous workflows that adapt based on the results that are obtained. A shared microservice for active learning prevents duplicated effort by each application team implementing its own adaptive design of experiments tool.

Drane, Lance [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2021

The cosmological evolution of self-interacting dark matter

We study the evolution of cosmological perturbations in dark-matter models with elastic and velocity-independent self interactions. Such interactions are imprinted in the matter-power spectrum as dark acoustic oscillations, which can be experimentally explored to determine the strength of the self scatterings. Models with self interactions have similarities to warm dark matter, as they lead to suppression of power on small scales when the dark-matter velocity dispersion is sizable. Nonetheless, both the physical origin and the extent of the suppression differ for self-interacting dark matter from conventional warm dark matter, with a dark sound horizon controlling the reduction of power in the former case, and a free-streaming length in the latter. We thoroughly analyze these differences by performing computations of the linear power spectrum using a newly developed Boltzmann code. We find that while current Lyman-α data disfavor conventional warm dark matter with a mass less than 5.3 keV, when self interactions are included at their maximal value consistent with bounds from the Bullet Cluster, the limits are relaxed to 4.4 keV. Lastly, we make use of our analysis to set novel bounds on light scalar singlet dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A General Framework for Error-controlled Unstructured Scientific Data Compression

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression ratios. We present a multi-component, error-bounded compression framework designed to enhance the compression of floating-point unstructured mesh data, which is common in scientific applications. Our approach involves interpolating mesh data onto a rectilinear grid and then separately compressing the grid interpolation and the interpolation residuals. This method is general, independent of mesh types and typologies, and can be seamlessly integrated with existing lossy compressors for improved performance. We evaluated our framework across twelve variables from two synthetic datasets and two real-world simulation datasets. The results indicate that the multi-component framework consistently outperforms state-of-the-art lossy compressors on unstructured data, achieving, on average, a 2.3 − 3.5× improvement in compression ratios, with error bounds ranging from 1 × 10 the −6 to 1×10−2. We further investigate impact of hyperparameters, such as grid spacing and error allocation, to deliver optimal compression ratios in diverse datasets.

Gong, Qian↗
DOE OSTI2025

Uncovering Sequence and Structural Characteristics of Fungal Expansin‐Related Proteins With Potential to Drive Substrate Targeting

Expansins loosen plant cell wall networks through disrupting non-covalent bonds between cellulose microfibrils and matrix polysaccharides. Whereas expansins were first discovered in plants, expansin-related proteins have since been identified in bacteria and fungi. The biological function of microbial expansins remains unclear; however, several studies have shown distinct binding preferences toward different structural polysaccharides. Earlier studies of bacterial expansin-related proteins uncovered sequence and structural features that correlate to substrate binding. Herein, 20 fungal expansin-related sequences were recombinantly produced in Komagataella phaffii, and the purified proteins were compared in terms of substrate binding to cellulosic and chitinous substrates. The impact of pH on the zeta potential of prioritized substrates was also measured, and Principal Component Analysis was performed to uncover correlations between protein characteristics (e.g., pI, hydrophobicity, surface charge distribution) and measured substrate binding preferences. Whereas acidic proteins with a predicted pI less than 5.0 preferentially bound to chitin, basic proteins with pI greater than 8.0 preferentially bound to xylan and xylan-containing fiber. Similar to many cellulases, binding to cellulose was correlated to relatively high aromatic amino acid content in the protein sequence and presence of a carbohydrate binding module (CBM), which in the case of expansins is a C-terminal CBM63. Whereas overall sequence characteristics could be correlated to substrate binding preference, the identity of amino acids occupying conserved positions that impact protein activity was better correlated with loosenin versus expansin classifications.

chitin↗
DOE OSTI2023

Biocatalytic control of site-selectivity and chain length-selectivity in radical amino acid halogenases

Biocatalytic C–H activation has the potential to merge enzymatic and synthetic strategies for bond formation. Fe II /αKG-dependent halogenases are particularly distinguished for their ability both to control selective C–H activation as well as to direct group transfer of a bound anion along a reaction axis separate from oxygen rebound, enabling the development of new transformations. In this context, we elucidate the basis for the selectivity of enzymes that perform selective halogenation to yield 4-Cl-lysine (BesD), 5-Cl-lysine (HalB), and 4-Cl-ornithine (HalD), allowing us to probe how site-selectivity and chain length selectivity are achieved. We now report the crystal structure of the HalB and HalD, revealing the key role of the substrate-binding lid in positioning the substrate for C 4 vs C 5 chlorination and recognition of lysine vs ornithine. Targeted engineering of the substrate-binding lid further demonstrates that these selectivities can be altered or switched, showcasing the potential to develop halogenases for biocatalytic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Block Lanczos algorithm for lattice QCD spectroscopy and matrix elements

Recent work introduced a new framework for analyzing correlation functions with improved convergence and signal-to-noise properties, as well as rigorous quantification of excited-state effects, based on the Lanczos algorithm and spurious eigenvalue filtering with the Cullum-Willoughby test. Here, we extend this framework to the analysis of correlation-function matrices built from multiple interpolating operators in lattice quantum chromodynamics (QCD) by constructing an oblique generalization of the block Lanczos algorithm, as well as a new physically motivated reformulation of the Cullum-Willoughby test that generalizes to block Lanczos straightforwardly. The resulting block Lanczos method directly extends generalized eigenvalue problem (GEVP) methods, which can be viewed as applying a single iteration of block Lanczos. Block Lanczos provides qualitative and quantitative advantages over GEVP methods analogous to the benefits of Lanczos over the standard effective mass, including faster convergence to ground- and excited-state energies, explicitly computable two-sided error bounds, straightforward extraction of matrix elements of external currents, and asymptotically constant signal-to-noise. No fits or statistical inference are required. Proof-of-principle calculations are performed for noiseless mock-data examples as well as two-by-two proton correlation-function matrices in lattice QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Running Primal-Dual Gradient Method for Time-Varying Nonconvex Problems

This paper focuses on a time-varying constrained nonconvex optimization problem, and considers the synthesis and analysis of online regularized primal-dual gradient methods to track a Karush-Kuhn-Tucker (KKT) trajectory. The proposed regularized primal-dual gradient method is implemented in a running fashion, in the sense that the underlying optimization problem changes during the execution of the algorithms. In order to study its performance, we first derive its continuous-time limit as a system of differential inclusions. We then study sufficient conditions for tracking a KKT trajectory, and also derive asymptotic bounds for the tracking error (as a function of the time-variability of a KKT trajectory). Further, we provide a set of sufficient conditions for the KKT trajectories not to bifurcate or merge, and also investigate the optimal choice of the parameters of the algorithm. Illustrative numerical results for a time-varying nonconvex problem are provided.

differential inclusion↗
DOE OSTI2022

CovS inactivation reduces CovR promoter binding at diverse virulence factor encoding genes in group A Streptococcus

The control of virulence gene regulator (CovR), also called caspsule synthesis regulator (CsrR), is critical to how the major human pathogen group A Streptococcus fine-tunes virulence factor production. CovR phosphorylation (CovR~P) levels are determined by its cognate sensor kinase CovS, and functional abrogating mutations in CovS can occur in invasive GAS isolates leading to hypervirulence. Presently, the mechanism of CovR-DNA binding specificity is unclear, and the impact of CovS inactivation on global CovR binding has not been assessed. Thus, we performed CovR chromatin immunoprecipitation sequencing (ChIP-seq) analysis in the emm1 strain MGAS2221 and its CovS kinase deficient derivative strain 2221-CovS-E281A. We identified that CovR bound in the promoter regions of nearly all virulence factor encoding genes in the CovR regulon. Additionally, direct CovR binding was observed for numerous genes encoding proteins involved in amino acid metabolism, but we found limited direct CovR binding to genes encoding other transcriptional regulators. The consensus sequence AATRANAAAARVABTAAA was present in the promoters of genes directly regulated by CovR, and mutations of highly conserved positions within this motif relieved CovR repression of the hasA and MGAS2221_0187 promoters. Analysis of strain 2221-CovS-E281A revealed that binding of CovR at repressed, but not activated, promoters is highly dependent on CovR~P state. CovR repressed virulence factor encoding genes could be grouped dependent on how CovR~P dependent variation in DNA binding correlated with gene transcript levels. Taken together, the data show that CovR repression of virulence factor encoding genes is primarily direct in nature, involves binding to a newly-identified DNA binding motif, and is relieved by CovS inactivation. These data provide new mechanistic insights into one of the most important bacterial virulence regulators and allow for subsequent focused investigations into how CovR-DNA interaction at directly controlled promoters impacts GAS pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

NDE Technology Engineering Program for Hanford DST Non-Visual Volumetric Inspection Technology: Phase II RAVIS Radiation Tolerance Test Report

This test report provides the results of radiation tolerance robustness testing that was performed on samples of robotic components and an ultrasonic guided wave air-slot sensor that represent components/sub-systems of the Robotic Air-slot Volumetric Inspection System (RAVIS) that has been engineered for volumetric inspection of Hanford tank bottom plates via under-tank refractory pad air-slots. The specific components tested for 1) functionality during active irradiation and 2) tolerance to cumulative radiation dose (until failure or upon reaching a cumulative dose test limit) were: • four samples each of a printed circuit board (PCB) and direct current (DC) motor, which are robotic components, and • 26 ultrasonic piezoelectric elements (samples) inside an air-slot sensor. The robotic components are part of the RAVIS air-slot inspection crawler drive control system that is responsible for remote communication with and actuation of the air-slot inspection crawler. The failure of either of these components during under-tank deployment would require manual retrieval via the crawler’s tether, which risks damage to the robot/refractory/tank. Preemptive replacement of the components at appropriately conservative dose/time intervals informed by failure dose would reduce the likelihood of under-tank failure. The components were included in radiation tolerance testing to quantify their failure doses to inform replacement intervals. The air-slot sensor is responsible for collecting ultrasonic inspection data (scan images) for the tank bottom plates during under-tank deployment. Compromised signal quality due to elevated noise levels caused by gamma radiation would compromise inspection performance. The air-slot sensor was included in radiation tolerance testing to quantify the impact of active irradiation on sensor signal quality. The irradiation and in-situ functional tests of the PCBs, DC motors and air-slot sensor took place in June and July 2020 at the Pacific Northwest National Laboratory. Testing was performed at a gamma dose rate near 300 rad/hr., which, in the absence of under-tank dose rate data, has been conservatively estimated to be the upper-bound dose rate beneath the primary tanks at Hanford. Irradiation took place at elevated temperatures of 150-200°F to determine failure doses that reflect the compounding effects of gamma radiation and heat. The test results revealed: • The DC motors can tolerate being actively irradiated at the high dose rate at 200°F and can tolerate a cumulative dose of 300,000 rad, that which would be incurred after 5 years of service at the 300 rad/hr dose rate. The component therefore meets minimum and preferred radiation tolerance and lifecycle requirements for robotic components. • The air-slot sensor can tolerate being actively irradiated at the high dose rate at 150°F and can tolerate a cumulative dose of 60,000 rad, that which would be incurred after 1 year of service at the 300 rad/hr dose rate. The sensor therefore meets minimum radiation tolerance and lifecycle requirements. • The PCB can tolerate being actively irradiated at the high dose rate, but can only tolerate a cumulative dose of 19,000 rad at 150-200°F. The PCB does not meet minimum radiation tolerance and lifecycle requirements; however, because the component is considered replaceable, it can be replaced before a cumulative dose of 19,000 rad is reached, determined through either monitoring with a dosimeter or scheduled time intervals that are calculated based on conservative estimates of under-tank dose rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Gravity-improved metastability bounds for the Type-I seesaw mechanism

Right-handed neutrinos (RHN) destabilize the electroweak vacuum by increasing its decay rate. In the SM, the latter is dominated by physics at the RG scale at which λ reaches its minimum, ${\mu}_{\ast}^{\textrm{SM}}$ ~10 17 GeV. For large neutrino Yukawa coupling Y ν , RHNs can push μ* beyond the Planck scale, implying that gravitational effects need to be taken into account. In this work, we perform the first comprehensive study of electroweak vacuum metastability in the type-I seesaw mechanism including these effects. Our analysis covers both low- and high-scale seesaw models, with two as well as three RHNs and for multiple values of the Higgs’ non-minimal coupling to gravity. We find that gravitational effects can significantly stabilize the vacuum, leading to weaker metastability bounds. We show that metastability sets the strongest bounds for low-scale seesaws with M N > 1 TeV. For high-scale seesaws, we find upper bounds on the allowed masses for the RHNs, which are relevant for high-scale leptogenesis. We also point out that Tr(${Y}_{\nu}^{\dagger}$Y ν ), which is commonly used to express these metastability bounds, cannot be used for all of parameter space. Instead, we argue that bounds can always be expressed reliably through Tr(${Y}_{\nu}^{\dagger}$Y ν ${Y}_{\nu}^{\dagger}$Y ν ). Lastly, we use this insight to develop a new technique for an easier RG analysis applicable to scenarios with degenerate RHN masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗