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DOE OSTI2018

Alternate Null Hypothesis Correlation: A New Approach to Automatic Seismic Event Detection

This paper describes a new method of seismic signal detection that improves upon the conventional waveform correlation method. Recent studies suggested that a significant limiting factor in the application of waveform correlation to regional and global scale monitoring is the false alarm rate. The false alarms do not originate from detections on noise but rather from seismic arrivals with unrelated source locations. This article presents results from an approach to waveform correlation that exploits techniques from signal processing and machine learning to improve the accuracy of detecting seismic arrivals. We modify the detection model for waveform correlation such that transient signals from noncollocated seismicity are considered when designing the detectors. The new approach uses waveform templates from known catalog events to train a supervised machine learning algorithm that derives a new set of detectors to represent the unique characteristics of the template waveforms; these new detectors maximize the likelihood of detecting only the desired events, thereby minimizing false alarms. We train a waveform correlation template library for a single three-component seismic monitoring station. We then review results from applying the new detectors, known as alternate null hypothesis correlation (ANCorr) templates, to a test set of seismic waveforms. Finally, we compare ANCorr results with those from application of the conventional waveform correlation matched filter technique.

58 GEOSCIENCES↗

DOE OSTI2019

Microstructural Characterization of Pure Tin Produced by the Drop-on-Demand Technique of Liquid Metal Jetting

The microstructure–property relationship of a pure tin part built using the drop-on-demand technique of liquid metal jetting, a cost–effective alternative to selective laser-melting or sintering techniques, was determined. Here, the microstructure of the as-built tin is observed to have minimal stored strain, low dislocation density, few to no voids, and the presence of only the β-tin phase; concurrently, mechanical properties are shown to be identical to the traditionally manufactured tin.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Electric field enhanced diffusion welding of alloy 617: Microstructural characteristics and mechanical properties

This study investigated the microstructural characteristics and mechanical behavior of diffusion welded nickel-based Alloy 617 obtained by electric field-assisted sintering (EFAS) using various parameters. The interfacial microstructure exhibited different characteristics including good grain boundary (GB) migration across the interface in the samples diffusion-welded at 1100 °C and a flat interface in the samples joined at 1000 °C and 1050 °C. The interface consisted of fine Al 2 O 3 oxides, while precipitation of interfacial M 23 C 6 carbides was not observed. Grain boundaries migrated across the Al 2 O 3 oxides, leaving these oxides within the grains. Graded grain size was observed, with grain coarsening being more significant near the sample surface due to the temperature gradient induced by EFAS. Tensile testing revealed that the specimens fractured in the matrix away from the interface, indicting strong diffusion-welded joints. Further, the peak tensile strength of 807 MPa was obtained in the samples welded at 1000 °C due to minimal grain growth. The materials obtained at 1100 °C exhibited reduced tensile strength but improved ductility. Strain maps revealed by digital image correlation showed alternating high and low strain segments in the samples produced at 1000 °C and 1050 °C, indicating that the flat interfaces with no GB migration were less ductile compared to the matrix. A greater strain uniformity was observed along the bond interfaces with improved GB migration. The hardness reduced near the sample surfaces due to enlarged grains induced by temperature gradient. This study demonstrates that GB migration and enhanced mechanical strength can be achieved in diffusion-welded Alloy 617.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Accelerating the convergence of auxiliary-field quantum Monte Carlo in solids with optimized Gaussian basis sets

We investigate the use of optimized correlation-consistent Gaussian basis sets for the study of insulating solids with auxiliary-field quantum Monte Carlo (AFQMC). The exponents of the basis set are optimized through the minimization of the second-order Møller–Plesset perturbation theory (MP2) energy in a small unit cell of the solid. We compare against other alternative basis sets proposed in the literature, namely, calculations in the Kohn–Sham basis and in the natural orbitals of an MP2 calculation. We find that our optimized basis sets accelerate the convergence of the AFQMC correlation energy compared to a Kohn–Sham basis and offer similar convergence to MP2 natural orbitals at a fraction of the cost needed to generate them. We also suggest the use of an improved, method independent, MP2-based basis set correction that significantly reduces the required basis set sizes needed to converge the correlation energy. With these developments, we study the relative performance of these basis sets in LiH, Si, and MgO and determine that our optimized basis sets yield the most consistent results as a function of volume. Using these optimized basis sets, we systematically converge the AFQMC calculations to the complete basis set and thermodynamic limit and find excellent agreement with experiment for the systems studied. Although we focus on AFQMC, our basis set generation procedure is independent of the subsequent correlated wavefunction method used.

Morales, Miguel A. (ORCID:0000000263893067)↗

DOE OSTI2025

Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data

The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces. Traditional methods based on the quantum description of the electronic structure, while widely used, are computationally expensive and demand substantial expertise. Emerging universal machine learning interatomic potentials (uMLIPs) offer a transformative alternative by employing pre-trained neural network surrogates to predict interatomic forces directly from atomic coordinates. This approach dramatically reduces computation time and minimizes the need for technical knowledge. In this paper, we produce a phonon database comprising nearly 5000 inorganic crystals to benchmark the performance of several leading uMLIPs. We further assess these models in real-world applications by using them to analyze experimental inelastic neutron scattering data collected on a variety of materials. Through detailed comparisons, we identify the strengths and limitations of these uMLIPs, providing insights into their accuracy and suitability for fast calculations of phonons and related properties, as well as the potential for real-time interpretation of neutron scattering spectra. Our findings highlight how the rapid advancement of AI in science is revolutionizing experimental research and data analysis.

inelastic neutron scattering↗

DOE OSTI2024

Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation

Deep learning architectures have achieved state-of-the-art (SOTA) performance on computer vision tasks such as object detection and image segmentation. This may be attributed to the use of over-parameterized, monolithic deep learning architectures executed on large datasets. Although such large architectures lead to increased accuracy, this is usually accompanied by a larger increase in computation and memory requirements during inference. While this is a non-issue in traditional machine learning (ML) pipelines, the recent confluence of machine learning and fields like the Internet of Things (IoT) has rendered such large architectures infeasible for execution in low-resource settings. For some datasets, large monolithic pipelines may be overkill for simpler inputs. To address this problem, previous efforts have proposed decision cascades where inputs are passed through models of increasing complexity until the desired performance is achieved. However, we argue that cascaded prediction leads to sub-optimal throughput and increased computational cost due to wasteful intermediate computations. To address this, we propose PaSeR (Parsimonious Segmentation with Reinforcement Learning) a non-cascading, cost-aware learning pipeline as an efficient alternative to cascaded decision architectures. Through experimental evaluation on both real-world and standard datasets, we demonstrate that PaSeR achieves better accuracy while minimizing computational cost relative to cascaded models. Further, we introduce a new metric IoU/GigaFlop to evaluate the balance between cost and performance. On the real-world task of battery material phase segmentation, PaSeR yields 179% improvement over SOTA MatPhase model and a 196% improvement over IDK Cascades under the IoU/GigaFlop metric. We also demonstrate PaSeR’s adaptability to complementary models trained on a noisy MNIST dataset, where it outperforms all baselines on IoU/GigaFlop by an average of 44%.

Srikshan, Bharat↗

DOE OSTI2018

Brazing Dissimilar Metals with a Novel Composite Foil

Reactive brazing is a novel technique in the joining industry that uses reactive materials to produce substantial amounts of heat locally to join components. In this project, we created mechanically processed dilute thermite foils (Redox Foils) that upon ignition selfpropagate to produce molten metal capable of joining dissimilar metal combinations. Due to the transient nature of the reaction, there is limited thermal damage to the base materials. Also, novel component combinations, that cannot be joined via tradition furnace brazing (such as magnesium alloys to steel), can be produced. Redox Foils are produced by mechanically processing and consolidating constituent powders. By adjusting the fabrication pathway and chemistry, the reaction products can be tailored to join specific material combinations. In addition to producing mechanically processed foils, we produce vapor processed foils with controlled microstructures to understand some of the mechanisms of the reaction. Over the course of the program, we worked to identify and enhance the properties of the Redox Foils so that they could produce strong braze bonds of dissimilar metals (steel, Al, and Mg alloys). In a first step, the reactivity of the powders, from which the foils were made, was enhanced by ball milling Al and metal oxide powders before consolidation. In a second step, Redox Foils were made by physical vapor deposition to identify what level of dilution is needed to prevent the formation of Cu vapor during the reaction of the Redox Foils. In a third step, we incorporated diluent powders within the milling process to improve homogeneity within the final foils. In addition, finite element model simulations of heat transfer were also combined with detailed microstructure studies to identify what level of homogeneity is needed to avoid the generation of Cu vapor. Lastly, we include Ag powders as a diluent to form a lower melting temperature braze. Unfortunately, none of these steps led to Redox Foils that could produce bonds with shear strengths greater than 10 MPa. The generation of oxygen vapor appears to be generating porous bond lines that are still relatively week. To circumvent this vapor generation, we investigated Ti:2B reactive scaffolds that provide a heated framework to enhance braze flow and minimize porosity. However, BM Ti:2B powders suffered ~8% mass loss due to surface adsorbed water resulting in porous and weak bonds. As an alternative solution, we developed Ti-C-Cu based reactive braze foils that rely on TiC formation reactions to melt the Cu braze material. In this system, the foils did not produce gas or vapor upon reaction but did form the desired TiC product with molten Cu. Unfortunately, the reaction temperatures and the duration of Cu melting were insufficient to produce effective bonds. The goal of achieving bond strengths of 20 MPa or higher was not achieved.

36 MATERIALS SCIENCE↗

NASA NTRS1990

Three-Zone Programmable Temperature Controller

Microprocessor-based controller regulates electrical power supplied to heater in each zone of three-zone directional-solidification furnace. Intended primarily for use in microgravity experiments aboard KC-135 airplane, controller also used on ground. Offers advantage of low electrical noise and consequent minimal interference with low-level signals put out by thermocouples and other sensors used in experiments. Achieved by heating with direct (instead of alternating) current and not pulsing heating current.

Smith, Guy A.↗

NASA NTRS1998

A 90 GHz Amplifier Assembled Using a Bump-Bonded InP-Based HEMT

We report on the performance of a novel W-band amplifier fabricated utilizing very compact bump bonds. We bump-bonded a high-speed, low-noise InP high electron mobility transistor (HEMT) onto a separately fabricated passive circuit having a GaAs substrate. The compact bumps and small chip size were used for efficient coupling and maximum circuit design flexibility. This new quasi-monolithic millimeter-wave integrated circuit (Q-MMIC) amplifier exhibits a peak gain of 5.8 dB at approx. 90 GHz and a 3 dB bandwidth of greater than 25%. To our knowledge, this is the highest frequency amplifier assembled using bump-bonded technology. Our bump-bonding technique is a useful alternative to the high cost of monolithic millimeter-wave integrated circuits (MMIC's). Effects of the bumps on the circuit appear to be minimal. We used the simple matching circuit for demonstrating the technology - future circuits would have all of the elements (resistors, via holes, bias lines, etc.) included 'in conventional MMIC's. Our design in different from other investigators' efforts in that the bumps are only 8 microns thick by 15 microns wide. The bump sizes were sufficiently small that the devices, originally designed for W-band hybrid circuits, could be bonded without alteration. Figure 3 shows the measured and simulated magnitude of S-parameters from 85-120 GHz, of the InP HEMT bump-bonded to the low noise amplifier (LNA) passive. The maximum gain is 5.8 dB at approx. 90 GHz, and gain extends to 117 GHz. Measurement of a single device (without matching networks) shows approx. 1 dB of gain at 90 GHz. The measured gain of the amplifier agrees well with the design in the center of the measurement band, and the agreement falls off at the band edges. Since no accommodation for the bump-bonding parasitics was made in the design, the result implies that the parasitic elements associated with the bonding itself do not dominate the performance of the LNA circuit. It should be noted that this amplifier was designed for good noise performance, which is why the input and output return losses are poorer than one would expect for an amplifier simply matched for gain. However, noise performance has not been measured at this time. While the agreement between modeled vs. experimental data is not exact, the data prove that bump-bonded technology can be used for amplifiers at frequencies at least as high as 100 GHz. JPL is pursuing this technology as a way to economically and quickly incorporate the best available HEMTs into a circuit with all of the reliability and circuit design flexibility offered by MMIC technology. We are currently using the technology to fabricate 4-stage, wide-band, W-band LNA's. We have also performed pull and shear tests which show that the bump bonds are sufficiently robust for any anticipated application.

Pinsukanjana, Paul R.↗

NASA NTRS1997

Sensory Interactive Teleoperator Robotic Grasping

As the technological world strives for efficiency, the need for economical equipment that increases operator proficiency in minimal time is fundamental. This system links a CCD camera, a controller and a robotic arm to a computer vision system to provide an alternative method of image analysis. The machine vision system which was employed possesses software tools for acquiring and analyzing images which are received through a CCD camera. After feature extraction on the object in the image was performed, information about the object's location, orientation and distance from the robotic gripper is sent to the robot controller so that the robot can manipulate the object.

Alark, Keli↗

NASA NTRS2013

Design Issues for Using Magnetic Materials in Radiation Environments at Elevated Temperature

One of the challenges of designing motors and alternators for use in nuclear powered space missions is accounting for the effects of radiation. Terrestrial reactor power plants use distance and shielding to minimize radiation damage but space missions must economize volume and mass. Past studies have shown that sufficiently high radiation levels can affect the magnetic response of hard and soft magnetic materials. Theoretical models explaining the radiation-induced degradation have been proposed but not verified. This paper reviews the literature and explains the cumulative effects of temperature, magnetic-load, and radiation-level on the magnetic properties of component materials. Magnetic property degradation is very specific to alloy choice and processing history, since magnetic properties are very much entwined with specific chemistry and microstructural features. However, there is basic theoretical as well as supportive experimental evidence that the negative impact to magnetic properties will be minimal if the bulk temperature of the material is less than fifty percent of the Curie temperature, the radiation flux is low, and the demagnetization field is small. Keywords: Magnets, Permanent Magnets, Power Converters, Nuclear Electric Power Generation, Radiation Tolerance.

Bowman, Cheryl L.↗

DOE OSTI2017

Direct SN Treatment of the Scattering Source with Phase Functions

In deterministic transport, the scattering operator is commonly expressed using a spherical harmonics (pn) expansion of the scattering source. Not only does this require minimal modifications if the problem dimensionality is changed, but it also contains little to no approximation whenever the scattering anisotropy degree is small. An alternative method relying on a discrete ordinates (sn) approach -- essentially computing the angular integral of the phase function with a finite number of weighted directions -- is theoretically possible and has shown some advantages. In particular, this method was introduced for neutron elastic scattering and was shown to be more accurate for highly anisotropic group-to-group transfer cross-sections. Benefits were further shown in the case of a collimated beam in highly forward peaked scattering media, particularly reducing the memory usage by storing an angle-to-angle collision matrix rather than a large number of angular moments. In addition, the scattering source was expressed using that same method, the phase function having been previously expanded using Legendre polynomials, in the context of achieving extreme precision while solving the 1D radiative transfer equation. Based on these previous works, we aim at exploring two questions. First, we wish to derive an expression of the phase function in reduced geometries that does not require any more angular quadrature points than for a standard sn calculation. This is particularly relevant in 2-D problems where the reduced phase function does not solely depend on the product of the incoming and outgoing directions. Second, we wish to better understand the relationship between the sn and pn treatments. We in particular show equivalence if the phase function in the former case is expanded Legendre polynomials. This equivalence is verified numerically and the computational costs of the methods are compared on a test problem involving a Dirac delta phase function.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Direct S{sub N} Treatment of the Scattering Source with Phase Functions

In deterministic transport, the angular dependency of the scattering source is described using a so-called phase function. The scattering operator is commonly expressed using a spherical harmonics (P{sub N}) expansion of this phase function. Not only does this require minimal modifications if the problem dimensionality is changed, but it also contains little to no approximation whenever the scattering anisotropy degree is small. An alternative method relying on a discrete ordinates (S{sub N}) approach - essentially computing the angular integral of the phase function with a finite number of weighted directions - is theoretically possible and has shown some advantages. In particular, this method was introduced for neutron elastic scattering and was shown to be more accurate for highly anisotropic group-to-group transfer cross-sections. Benefits were further shown in the case of a collimated beam in highly forward peaked scattering media, particularly reducing the memory usage by storing an angle-to-angle collision matrix rather than a large number of angular moments. In addition, the scattering source was expressed using that same method, the phase function having been previously expanded using Legendre polynomials, in the context of achieving extreme precision while solving the 1D radiative transfer equation. Based on these previous works, we aim at exploring two questions. First, we wish to derive an expression of the phase function in reduced geometries that does not require any more angular quadrature points than for a standard S N calculation. This is particularly relevant because the reduced phase function does not solely depend on the product of the incoming and outgoing directions. Second, we wish to better understand the relationship between the S{sub N} and P{sub N} treatments. We in particular show equivalence if the phase function in the former case is expanded Legendre polynomials. This equivalence is verified numerically and the computational costs of the methods are compared on a test problem involving a Dirac delta phase function.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Toward a scalable robust security-constrained optimal power flow using a proximal projection bundle method

Robust security-constrained optimal power flow (rSCOPF) aims to find the worst-case contingencies of alternating current optimal power flow (ACOPF) in power systems. With the rise of GPU architectures on the upcoming supercomputer architectures, optimization algorithms that rely on sparse linear algebra and indefinite linear systems are becoming increasingly hard to solve efficiently (e.g. interior-point method). To address this we revisit a maximin optimization formulation of the rSCOPF and the single-level mixed-integer semidefinite programming (MISDP) reformulation, which is obtained by taking the Lagrangian relaxation of the inner minimization ACOPF problem. In this paper, we focus on the development of a proximal projection bundle method (PPBM) for solving continuous relaxation node subproblems of the MISDP problem, based primarily on the well-known alternating direction method of multipliers. Cutting planes reminiscent of bundle method ideas are also applied in coordination with updates of the proximal parameter. The cutting-plane method can generate a large number of linear inequalities, leading to a large scale but decomposable quadratic programming (QP) subproblem that is amenable to GPUs. We present the numerical results on the IEEE 30, 57, 118, and 300-bus systems by using our PBMM method. We discuss the main computational bottleneck of our method, which is the time taken to solve each iteration of a QP subproblem instance of the PPBM, and how GPU architectures can accelerate this solution process.

bundle method↗

DOE OSTI2013

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece

Highlights: • A two-step (strategic and detailed optimal planning) methodology is used for solving complex MSW management problems. • A software package is outlined, which can be used for generating detailed optimal plans. • Sensitivity analysis compares alternative scenarios that address objections and/or wishes of local communities. • A case study shows the application of the above procedure in practice and demonstrates the results and benefits obtained. - Abstract: The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/or wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to: (a) serve 113 Municipalities and Communities that generate nearly 2 million t/y of comingled MSW with distinctly different waste collection patterns, (b) take into consideration several existing waste transfer stations (WTS) and optimize their use within the overall plan, (c) select the most appropriate sites among the potentially suitable (new and in use) ones, (d) generate the optimal profile of each WTS proposed, and (e) perform sensitivity analysis so as to define the impact of selected sets of constraints (limitations in the availability of sites and in the capacity of their installations) on the design and cost of the ensuing optimal waste transfer system. The results show that optimal planning offers significant economic savings to municipalities, while reducing at the same time the present levels of traffic, fuel consumptions and air emissions in the congested Athens basin.

42 ENGINEERING↗

DOE OSTI2023

Prediction and uncertainty quantification of shale well performance using multifidelity Monte Carlo

Uncertainty quantification is an integral component of reservoir management, especially considering the inherent uncertainty in subsurface systems. While a standard practice to estimate the uncertainty, Monte Carlo (MC) simulation is computationally intense when the sampling population comprises high-fidelity simulations. Alternatively, the Multi-fidelity Monte Carlo (MFMC) simulation overcomes this computational intensity by integrating low- and high-fidelity simulations. Our goal is to minimize the number of expensive high-fidelity simulations while maintaining accuracy and using numerous fast and cheap low-fidelity simulations to efficiently sample to input parameter space of interest. We selected gas production from unconventional wells to demonstrate the potential speedups and accuracy of the MFMC approach. The model fidelity usually determines the trade-off between accuracy and efficiency. While the high-fidelity model is more accurate, the low-fidelity model is more efficient. Our high-fidelity simulation includes reservoir simulations of a hydraulically fractured well. On the other hand, our low-fidelity model comprises the parallel-plate flow model. We used differential programming to efficiently solve the 1D flow model, where automatic differentiation is used to efficiently compute the gradients. We matched the production profile of high-fidelity simulations with our low-fidelity simulations. Then, we used a support vector regression to map the high- and low-fidelity input parameters. The mapping function is essential to tune the low-dimensional parameter space of the low-fidelity model to the high-dimensional parameter space of the high-fidelity model. We found that we can use a combination of 9 high fidelity and 10,000 low fidelity simulations to efficiently and accurately simulate pressure management. This method is at least two orders of magnitude faster than only using high-fidelity simulations. Finally, from a broader perspective, MFMC could efficiently estimate the uncertainty of various systems and models, integrating low- and high-fidelity models.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2021

Transmission of Images on High-Temperature Nuclear-Grade Metallic Pipe with Ultrasonic Elastic Waves

Transmission of information using elastic ultrasonic waves on existing metallic pipes provides an alternative communication option for a nuclear facility. The advantages of this approach consist of transmitting information through barriers, such as the containment building wall, with minimal modification of the existing hardware. Because bit rates on the order of kilobits per second are achievable, relatively large volumes of data, such as images, can be transmitted. A viable candidate for an ultrasonic communication channel is a stainless steel pipe of the chemical volume control system (CVCS) that penetrates through the reactor containment building wall through a sealed tunnel. To study ultrasonic communication under simulated nuclear facility conditions of high temperature, a test article was developed by installing heating tapes, temperature controllers, and thermal insulation on a laboratory CVCS-like stainless steel pipe. High temperature and radiation-resilient lithium niobate ultrasonic transducers were utilized for information transmission on the heated pipe. The amplitude shift keying (ASK) digital communication protocol was developed and implemented in a GNU Radio software-defined radio environment. A root-raised-cosine filter was introduced to suppress ultrasonic transducer ringing and thus reduce inter-symbol interference. This resulted in the enhancement of the data transmission bit rate compared to information encoding with square pulses. Demonstrations of communication at high temperature included transmission of a 90-KB image at the bit rate of 10 Kbps with a bit error rate of 10 -3 across a 6-ft-long straight pipe heated up to 230 degrees C. Additional preliminary studies were conducted to evaluate ultrasonic communication system resilience to environmental degradation and damage.

42 ENGINEERING↗

DOE OSTI2024

Random matrix model of the Virasoro minimal string

The model of two dimensional quantum gravity defining the Virasoro minimal string, presented recently by Collier, Eberhardt, Mühlmann, and Rodriguez, was also shown to be perturbatively (in topology) equivalent to a random matrix model. An alternative definition is presented here, in terms of double-scaled orthogonal polynomials, thereby allowing direct access to nonperturbative physics. Already at leading order, the defining string equation’s properties yield valuable information about the nonperturbative fate of the model, confirming that the case ( c = 25 , c ^ = 1 ) (central charges of spacelike and timelike Liouville sectors) is special, by virtue of sharing certain key features of the N = 1 supersymmetric JT gravity string equation. Solutions of the full string equation are constructed using a special limit, and the (Cardy) spectral density is completed to all genus and beyond. The distributions of the underlying discrete spectra are readily accessible too, as is the spectral form factor. Some examples of these are exhibited. Published by the American Physical Society 2024

Astronomy & Astrophysics↗