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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Observing dark matter decays to gravitons via graviton-photon conversion

Since dark matter is only known to have gravitational interactions, it may plausibly decay to gravitons on cosmological timescales. Although such a scenario can be easily realized, there are currently no known limits on this possibility based on indirect-detection methods. We propose a new search strategy that exploits the Gertsenshtein effect, whereby the gravitons produced in dark matter decays can convert to photons in large-scale magnetic fields along the line of sight to an observer. These conversions primarily occur within cosmological filaments which occupy a large (order unity) volume fraction and contain ∼ 10 – 100 nG fields with ∼ Mpc coherence lengths. Thus, dark matter decays to gravitons predict an irreducible population of extragalactic photons, which we constrain using the extragalactic gamma-ray background measured by the Fermi-LAT telescope. Using this method, we derive the first-ever constraints on the dark matter lifetime in the 0.1 GeV - 10 8 GeV mass range, contingent on the assumed filament magnetic field strength. We also make projections for the Advanced Particle-astrophysics Telescope, which can improve sensitivity to this dark matter decay channel by an order of magnitude beyond those we set using Fermi-LAT data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

stor4build

The EnergyPlus simulation engine supports modeling and simulation of thermal energy storage (TES) systems in several ways, including using the Python-EMS feature, which extends the operation of the engine with custom code written in Python. Creation of models using this feature can be tedious and error prone, with the connection of the model components to the Python code a particularly troublesome area. The stor4build Python package simplifies this process by modifying an input model to add a selected TES technology (implemented with the Python-EMS feature) and runs the simulation. The package leverages the OpenStudio middleware software development kit to automate this process as much as possible, eliminating potential errors and simplifying usage of EnergyPlus. The package provides objects, functions, and OpenStudio measures that implement the necessary operations to automate the creation of EnergyPlus models that integrate TES technologies with building systems. In addition, two user interfaces are provided: a command line interface and a web application programming interface. The automated process implemented by the package greatly simplifies the modeling and simulation process, allowing for parametric studies to be executed much more efficiently and effectively. The OpenStudio-based workflow is also very flexible and will allow for future additions of new technologies.

DeGraw, JasonWilliam [Oak Ridge National Laborator↗
DOE OSTI2023

An Overview of UME: Unstructured Mesh Explorations [Slides]

What is UME? UME extracts an important computational kernel from a large computational physics application, which is based on an unstructured mesh representation. The memory layout, indexing, data management, and communication patterns are as close to the original application as possible. The original application is a long-lived Fortran program, with ~750K source lines of code (sloc). UME is a C++17 implementation of a zone gradient operator, with about ~3K sloc.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Bioinformatic and Mechanistic Analysis of the Palmerolide PKS-NRPS Biosynthetic Pathway From the Microbiome of an Antarctic Ascidian

Complex interactions exist between microbiomes and their hosts. Increasingly, defensive metabolites that have been attributed to host biosynthetic capability are now being recognized as products of host-associated microbes. These unique metabolites often have bioactivity targets in human disease and can be purposed as pharmaceuticals. Polyketides are a complex family of natural products that often serve as defensive metabolites for competitive or pro-survival purposes for the producing organism, while demonstrating bioactivity in human diseases as cholesterol lowering agents, anti-infectives, and anti-tumor agents. Marine invertebrates and microbes are a rich source of polyketides. Palmerolide A, a polyketide isolated from the Antarctic ascidian Synoicum adareanum, is a vacuolar-ATPase inhibitor with potent bioactivity against melanoma cell lines. The biosynthetic gene clusters (BGCs) responsible for production of secondary metabolites are encoded in the genomes of the producers as discrete genomic elements. A candidate palmerolide BGC was identified from a S. adareanum microbiome-metagenome based on a high degree of congruence with a chemical structure-based retrobiosynthetic prediction. Protein family homology analysis, conserved domain searches, active site and motif identification were used to identify and propose the function of the ~75 kbp trans-acyltransferase (AT) polyketide synthase-non-ribosomal synthase (PKS-NRPS) domains responsible for the stepwise synthesis of palmerolide A. Though PKS systems often act in a predictable co-linear sequence, this BGC includes multiple trans-acting enzymatic domains, a non-canonical condensation termination domain, a bacterial luciferase-like monooxygenase (LLM), and is found in multiple copies within the metagenome-assembled genome (MAG). Detailed inspection of the five highly similar pal BGC copies suggests the potential for biosynthesis of other members of the palmerolide chemical family. This is the first delineation of a biosynthetic gene cluster from an Antarctic microbial species, recently proposed as Candidatus Synoicihabitans palmerolidicus. These findings have relevance for fundamental knowledge of PKS combinatorial biosynthesis and could enhance drug development efforts of palmerolide A through heterologous gene expression.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Performance of abiotic stress-inducible synthetic promoters in genetically engineered hybrid poplar (Populus tremula × Populus alba)

Abiotic stresses can cause significant damage to plants. For sustainable bioenergy crop production, it is critical to generate resistant crops to such stress. Engineering promoters to control the precise expression of stress resistance genes is a very effective way to address the problem. Here we developed stably transformed Populus tremula × Populus alba hybrid poplar (INRA 717-1B4) containing one-of-six s ynthetic d rought stress-inducible promoters (SDs; SD9-1, SD9-2, SD9-3, SD13-1, SD18-1, and SD18-3) identified previously by transient transformation assays. We screened green fluorescent protein (GFP) induction in poplar under osmotic stress conditions. Of six transgenic lines containing synthetic promoter, three lines (SD18-1, 9-2, and 9-3) had significant GFP expression in both salt and osmotic stress treatments. Each synthetic promoter employed heptamerized repeats of specific and short cis -regulatory elements (7 repeats of 7-8 bases). To verify whether the repeats of longer sequences can improve osmotic stress responsiveness, a transgenic poplar containing the synthetic promoter of the heptamerized entire SD9 motif (20 bases, containing all partial SD9 motifs) was generated and measured for GFP induction under osmotic stress. The heptamerized entire SD9 motif did not result in higher GFP expression than the shorter promoters consisting of heptamerized SD9-1, 9-2, and 9-3 (partial SD9) motifs. This result indicates that shorter synthetic promoters (~50 bp) can be used for versatile control of gene expression in transgenic poplar. These synthetic promoters will be useful tools to engineer stress-resilient bioenergy tree crops in the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Clustering redshift distribution calibration of weak lensing surveys using the DESI-DR1 spectroscopic dataset

We estimate the source redshift distribution of current weak lensing surveys by applying the clustering-based redshift calibration technique, using the galaxy redshift sample provided by the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1). We cross-correlate the Bright Galaxy Survey (BGS), Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) from DESI, within the redshift range $0.1 < z < 1.6$, with overlapping tomographic source samples from the Dark Energy Survey (DES), Kilo-Degree Survey (KiDS), and Hyper Suprime-Cam (HSC) survey. Using realistic mock catalogues, we test the stability of the clustering-redshift signal to fitting scale, reference-sample choice, and the evolution of source galaxy bias, and we explicitly model and marginalise over magnification contributions, which become non-negligible at $z \gtrsim 1$ due to the depth of the DESI ELG sample. We then compare the resulting bias-weighted redshift distributions to those calibrated using self-organising map (SOM) techniques, finding agreement within uncertainties for all surveys and tomographic bins. Our results demonstrate that clustering redshifts enabled by DESI's unprecedented spectroscopic sample provides a robust, complementary, and independent constraint capable of reducing one of the dominant systematic uncertainties in weak lensing cosmology.

Ruggeri, R. [Queensland U.]↗
DOE OSTI2024

Developing IEEE Std 2800-Compliant Algorithms for Transmission-Connected Inverter-Based Resources: Preprint

This study addresses the compliance of Inverter-based Resources (IBRs) with the IEEE Std 2800, a leading standard that defines interconnection and interoperability requirements for IBRs integrated into transmission systems. Focusing on abnormal grid scenarios, the research evaluates the specific demands on IBRs, proposing a comprehensive controller development framework. This framework caters to maintaining ride-trhough operation or implementing strategic disconnections in line with IEEE Std 2800, alongside managing currents during voltage ride-through scenarios. The effectiveness of this proposed controller framework is rigorously validated through case studies, employing a MATLAB/Simulink model of an IBR to test its performance under diverse grid fault conditions, ensuring the IBRs' alignment with standard requirements and their robust performance in enhancing grid reliability.

IEEE Std 2800↗
DOE OSTI2024

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

Rahman, Md Habibur (ORCID:000000027705984X)↗
DOE OSTI2025

Robust quantification of the diamond nitrogen-vacancy center charge state via photoluminescence spectroscopy

Nitrogen vacancy (NV) centers in diamond are at the heart of many emerging quantum technologies, all of which require control over the NV charge state. Hence, methods for quantification of the relative photoluminescence intensities of the NV 0 and NV − charge states, i.e., a charge state ratio, are vital. Several approaches to quantify NV charge state ratios have been reported but are either limited to bulk-like NV diamond samples or yield qualitative results. We propose an NV charge state quantification protocol based on the determination of sample- and experimental setup-specific NV 0 and NV − reference spectra. The approach employs blue (400–470 nm) and green (480–570 nm) excitation to infer pure NV 0 and NV − spectra, which are then used to quantify NV charge state ratios in subsequent experiments via least squares fitting. We test our dual excitation protocol (DEP) for a bulk diamond NV sample and 20 and 100 nm nanodiamond particles and compare results with those obtained via other commonly used techniques such as zero-phonon line fitting and non-negative matrix factorization. We find that DEP can be employed across different samples and experimental setups and yields consistent and quantitative results for NV charge state ratios that are in agreement with our understanding of NV photophysics. By providing robust NV charge state quantification across sample types and measurement platforms, DEP will support the development of NV-based quantum technologies.

Color center laser spectroscopy↗
DOE OSTI2025

Spatially resolved X-ray imaging and molecular characterisation of sulfur and iron in organic- and sulfur-rich hydrocarbon source mudstones

Sulfurisation of organic matter (OM) is a prominent preservation mechanism, however iron sulfide precipitation, particularly pyrite (FeS2), can counteract this mechanism. There is a dearth of high-resolution, spatially-resolved spectroscopic (redox) information on sulfur and iron inventories within organic-rich rocks that would improve our understanding of prevailing environmental conditions during deposition. Here, state-of-the-art synchrotron-based X-ray absorption and fluorescence analyses of key organic- and sulfur-rich mudstones demonstrate the potential of these techniques to non-destructively map and produce detailed spectroscopic information. Detailed high-resolution analyses (μm- to mm-scale) reveal the presence of widespread sulfurised OM in the Blackstone Band of the Kimmeridge Clay Formation, in line with a persistence of euxinia over a long temporal span and low reactive iron input, facilitating the preservation of OM through sulfurisation. In contrast, the presence of sulfurised OM was transitional in the Monterey Formation, consistent with fluctuating water column redox conditions, and is less significant in the Whitby Mudstone Formation, likely due to the high reactive iron concentrations outcompeting sulfurised OM formation. Analyses of sulfur species using model compounds further indicate that the Whitby Formation is strongly enriched in inorganic reduced sulfur minerals, while both the Kimmeridge Clay and Monterey Formations are dominated by organic sulfur species. These synchrotron-based observations improve our understanding of environmental conditions during the time of deposition of these mudstones and thus show great promise in the study of organic-rich sediments, especially in allowing their depositional settings to be more accurately reconstructed.

Kimmeridge Clay Formation↗
DOE OSTI2024

Alternating Direction Decomposition with Strong Bounding and Convexification (ADDSBC) for Solving Security Constrained AC Unit Commitment Problems

This project aims to develop efficient and robust computational methods for solving the security-constrained unit commitment and alternating current optimal power flow problem (SC-UC-ACOPF). The SC-UC-ACOPF problem is at the center of the short-term operation of the U.S. Power Grid. It is solved every week, every day, and every 10 minutes to plan for the optimal action of electricity generation and consumption by minimizing the generation cost and maintaining power system reliability against potential disruptions of equipment failures. In mathematical terms, SC-UC-ACOPF is a challenging large-scale mixed-integer nonlinear optimization model. This means that the decisions involve both discrete variables, e.g. the turning on and off of generators and switching of transmission lines and transformers, and continuous decisions, e.g. the amount of energy generated by each generator and the power flows in the power grid. The physics of the power flow is described by nonlinear equations involving real and reactive power and bus voltages. Another key feature is the large number of contingencies, i.e. the system needs to stay reliable in face of failure of any one equipment, such as transmission lines and generators. The U.S. power grids are extremely complicated and large scale with more than 5,000 generators, 50,000 buses, and 100,000 high-voltage transmission lines, making the SC-UC-ACOPF a very large-scale computation challenge. The research developed in this project aims to solve the SC-UC-ACOPF problems in the three timescales, i.e. weekly, daily, and every 10-min. The proposed computational methods are built on a principled algorithmic approach of decomposition and penalization. More specifically, the algorithm develops spatial and temporal decomposition by exploiting the strong temporal coupling and weak spatial coupling of the UC problem and the complementary feature, i.e. weak temporal coupling and strong spatial coupling of the ACOPF problem. The algorithm also leverages recent progresses in strong convex relaxation of ACOPF. A unique feature of the proposed approach is that it generates a valid, global upper bound on the optimal maximum profit. In this way, a global optimality gap is available to measure the quality of the solution. To further speed up computation, the research team has developed a plethora of effective heuristics to strengthen the iterative penalty-based decomposition framework. For instance, a heuristic is developed to construct inner approximations of the time coupling constraints within the time decoupled problems. Contingencies are pre-screened and low-rank matrix computation is exploited to find the almost unique solution to each contingency. A novel heuristic for line switching is proposed and tested with positive impacts on instances where line switching is beneficial. Taking a systematic approach and carefully handling every detail of the problem pays off. The TIM-GO’s performance throughout the trials and the final event was stellar. TIM-GO garnered the second highest total prize money and is ranked in the top three positions across all categories of comparison.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Glass-contact refractory of the nuclear waste vitrification melters in the United States: a review of corrosion data and melter life

The performance of the refractory lining in glass melters used for nuclear waste vitrification is critical to the melter reliability for long-term continuous operation. Monofrax® K-3, a high Cr 2 O 3 fused cast refractory material, has been widely used to build the liners of nuclear waste glass melters in the United States. Corrosion behaviour of Monofrax® K-3 refractory has been evaluated based on crucible-scale testing, inspection of the refractory components following scaled melter testing, and inspections of the Defense Waste Processing Facility (DWPF) melter refractory after service. The literature generally consists of empirical models based on short-term testing to describe refractory corrosion dependence on glass composition. Corrosion data from tests with longer testing times, at various temperatures, in the presence of molten salts, and with different redox reactions in the plenum atmosphere exist, may be insufficient to provide accurate refractory service life estimates. Additionally, the corrosion data collected under actual and scaled melter operating conditions are limited. Recommendations to achieve more direct correlation between the laboratory refractory corrosion data predictions and the observed melter service life are discussed to allow for more accurate predictions of the useful life of melter refractory linings.

Jin, Tongan↗
DOE OSTI2024

Artificial Intelligence Assisted Inversion (AIAI): Quantifying the Spectral Features of 56 Ni of Type Ia Supernovae

Abstract Following our previous study of Artificial Intelligence Assisted Inversion (AIAI) of supernova analyses, we train a set of deep neural networks based on the 1D radiative transfer code TARDIS to simulate the optical spectra of Type Ia supernovae (SNe Ia) between 10 and 40 days after the explosion. The neural networks are applied to derive the mass of 56 Ni in velocity ranges above the photosphere for a sample of 124 well-observed SNe Ia in the TARDIS model context. A subset of the SNe have multi-epoch observations for which the decay of the radioactive 56 Ni can be used to test the AIAI quantitatively. The 56 Ni mass derived from AIAI using the observed spectra as inputs for this subset agrees with the radioactive decay rate of 56 Ni. AIAI reveals that a spectral signature near 3890 Å is related to the Niii4067Å line, and the 56 Ni mass deduced from AIAI is found to be correlated with the light-curve shapes of SNe Ia, with SNe Ia with broader light curves showing larger 56 Ni mass in the envelope above the photosphere. AIAI enables spectral data of SNe to be quantitatively analyzed under theoretical frameworks based on well-defined physical assumptions.

Astronomy & Astrophysics↗
DOE OSTI2022

Reviewing clinical considerations and guideline recommendations of C1 inhibitor prophylaxis for hereditary angioedema

Abstract Background Hereditary angioedema (HAE), a rare disease that is characterized by painful and recurring non‐allergic swelling episodes, is caused by the deficiency or dysfunction of C1 inhibitor (C1INH) protein. A comprehensive HAE management plan may require long‐term prophylaxis (LTP) in addition to on‐demand treatment to help “normalize” patients' lives so that they may fully engage in work, school, family, and leisure activities. Aim The main objective of this narrative review is to provide an overview of updated guideline recommendations specific to LTP of HAE and discuss clinical considerations and pharmacologic management options, with a focus on C1INH. Materials and Methods The authors reviewed relevant HAE literature for current recommendations regarding LTP and the role of C1NH. Results Acute HAE attacks are treated with on‐demand medication; however, there is a consensus that LTP should routinely be considered for risk reduction and prevention of future episodes. The 2017 World Allergy Organization/European Academy of Allergy and Clinical Immunology guidelines recommend that all patients with HAE be evaluated for LTP routinely and the 2020 HAE Association (HAEA) guidelines emphasize that the decision to use LTP should not be based on rigid criteria, but rather should be based on individual patient needs. Both guidelines recommend C1INH as first‐line/preferred therapy for LTP in a range of patient types including adults, children/adolescents, and pregnant/lactating patients. The HAEA also recommends the kallikrein inhibitor, lanadelumab, as a first‐line option for LTP. HAE pathway‐specific agents for LTP have not been associated with notable safety concerns. Discussion Plasma‐derived C1INH has been available for 40+ years in Europe and impacts multiple targets within the HAE pathway. C1INH has been used for on‐demand treatment and LTP. A subcutaneous formulation of plasma‐derived C1INH is approved for LTP and produces functional C1INH activity levels consistently above the threshold needed for protection from HAE attacks. Other pathway‐specific options for LTP include the plasma kallikrein inhibitors, lanadelumab‐flyo and berotralstat, approved for adults and pediatric patients aged ≥12 years. C1INH is approved for adults and pediatric patients aged ≥6 years. Conclusion Assessing the need for LTP is vital in the ongoing dialogue between clinicians and patients, as both disease‐related factors and patient preferences may change over time. Among available options for LTP, plasma‐derived C1INH is the broadly recommended first‐line option for LTP in patients with HAE, including pregnant/lactating women and pediatric patients (≥6 years).

Anderson, John↗
DOE OSTI2022

Multidisciplinary Constraints on the Thermal‐Chemical Boundary Between Earth's Core and Mantle

Abstract Heat flux from the core to the mantle provides driving energy for mantle convection thus powering plate tectonics, and contributes a significant fraction of the geothermal heat budget. Indirect estimates of core‐mantle boundary heat flow are typically based on petrological evidence of mantle temperature, interpretations of temperatures indicated by seismic travel times, experimental measurements of mineral melting points, physical mantle convection models, or physical core convection models. However, previous estimates have not consistently integrated these lines of evidence. In this work, an interdisciplinary analysis is applied to co‐constrain core‐mantle boundary heat flow and test the thermal boundary layer (TBL) theory. The concurrence of TBL models, energy balance to support geomagnetism, seismology, and review of petrologic evidence for historic mantle temperatures supports Q CMB ∼15 TW, with all except geomagnetism supporting as high as ∼20 TW. These values provide a tighter constraint on core heat flux relative to previous work. Our work describes the seismic properties consistent with a TBL, and supports a long‐lived basal mantle molten layer through much of Earth's history.

58 GEOSCIENCES↗
DOE OSTI2023

Machine learning predictions of diffusion in bulk and confined ionic liquids using simple descriptors

Ionic liquids have many intriguing properties and widespread applications such as separations and energy storage. However, ionic liquids are complex fluids and predicting their behavior is difficult, particularly in confined environments. We introduce fast and computationally efficient machine learning (ML) models that can predict diffusion coefficients and ionic conductivity of bulk and nanoconfined ionic liquids over a wide temperature range (350–500 K). The ML models are trained on molecular dynamics simulation data for 29 unique ionic liquids as bulk fluids and confined in graphite slit pores. This model is based on simple physical descriptors of the cations and anions such as molecular weight and surface area. Here, we also demonstrate that accurate results can be obtained using only descriptors derived from SMILES (simplified molecular-input line-entry system) codes for the ions with minimal computational effort. This offers a fast and efficient method for estimating diffusion and conductivity of nanoconfined ionic liquids at various temperatures without the need for expensive molecular dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

DESI DR1 Ly α 1D power spectrum: the Fast Fourier Transform estimator measurement

Here, we present the one-dimensional Lyman-α forest power spectrum measurement derived from the data release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI). The measurement of the Lyman-α forest power spectrum along the line of sight from high-redshift quasar spectra provides information on the shape of the linear matter power spectrum, neutrino masses, and the properties of dark matter. In this work, we use a Fast Fourier Transform (FFT)-based estimator, which is validated on synthetic data in a companion paper. Compared to the FFT measurement performed on the DESI early data release, we improve the noise characterization with a cross-exposure estimator and test the robustness of our measurement using various data splits. We also refine the estimation of the uncertainties and now present an estimator for the covariance matrix of the measurement. Furthermore, we compare our results to previous high-resolution and eBOSS measurements. In another companion paper, we present the same DR1 measurement using the Quadratic Maximum Likelihood Estimator (QMLE). These two measurements are consistent with each other and constitute the most precise one-dimensional power spectrum measurement to date, while being in good agreement with results from the DESI early data release.

Lyman alpha forest↗
DOE OSTI2022

Detecting cosmic strings with lensed fast radio bursts

Correlated red noise recently reported from pulsar timing observations may be an indication of stochastic gravitational waves emitted by cosmic strings that formed during a primordial phase transition near the grand unification energy scale. Unfortunately, known probes of cosmic strings, namely the cosmic microwave background anisotropies and string lensing of extragalactic galaxies, are not sensitive enough for low dimensionless string tensions of Gμc -2 = 10 -10 – 10 -7 (where the tension μ is the string energy per unit length) that are needed to explain this putative signal. We show that strong gravitational lensing of fast radio bursts (FRBs) by cosmic strings is a potentially unambiguous avenue to probe that range of string tension values. The image pair of string lensing are expected to have identical magnification factor and parity, and have a typical time delay of ~10 2 (Gμc -2 /10 -8 ) 2 s. Here, the unique spectral fingerprint of each FRB, as well as the possibility to detect correlations in the time series of the electric field of the radio waves, will enable verification of the string lensing interpretation. Very-long-baseline interferometry observations can spatially resolve the image pair and provide a lower bound on the string tension based on the image separation. We calculate the FRB lensing rate as a function of the FRB detection number for several different models of the FRB redshift distribution. We find that a survey detecting ~10 5 FRBs, in line with estimates for the detection rate of the forthcoming survey CHORD, can uncover a strong lensing event for a string tension of Gμc -2 ≃ 10 -7 . Larger FRB surveys, such as Phase 2 of the Square Kilometre Array, have the potential to significantly improve the sensitivity on the string tension to Gμc -2 ≃ 10 -9 .

79 ASTRONOMY AND ASTROPHYSICS↗