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NASA NTRS1993

CRAY mini manual. Revision D

This document briefly describes the use of the CRAY supercomputers that are an integral part of the Supercomputing Network Subsystem of the Central Scientific Computing Complex at LaRC. Features of the CRAY supercomputers are covered, including: FORTRAN, C, PASCAL, architectures of the CRAY-2 and CRAY Y-MP, the CRAY UNICOS environment, batch job submittal, debugging, performance analysis, parallel processing, utilities unique to CRAY, and documentation. The document is intended for all CRAY users as a ready reference to frequently asked questions and to more detailed information contained in the vendor manuals. It is appropriate for both the novice and the experienced user.

Tennille, Geoffrey M.↗

NASA NTRS2006

Crew Launch Vehicle (CLV) Upper Stage Configuration Selection Process

The Crew Launch Vehicle (CLV), a key component of NASA's blueprint for the next generation of spacecraft to take humans back to the moon, is being designed and built by engineers at NASA s Marshall Space Flight Center (MSFC). The vehicle s design is based on the results of NASA's 2005 Exploration Systems Architecture Study (ESAS), which called for development of a crew-launch system to reduce the gap between Shuttle retirement and Crew Exploration Vehicle (CEV) Initial Operating Capability, identification of key technologies required to enable and significantly enhance these reference exploration systems, and a reprioritization of near- and far-term technology investments. The Upper Stage Element (USE) of the CLV is a clean-sheet approach that is being designed and developed in-house, with element management at MSFC. The USE concept is a self-supporting cylindrical structure, approximately 115' long and 216" in diameter, consisting of the following subsystems: Primary Structures (LOX Tank, LH2 Tank, Intertank, Thrust Structure, Spacecraft Payload Adaptor, Interstage, Forward and Aft Skirts), Secondary Structures (Systems Tunnel), Avionics and Software, Main Propulsion System, Reaction Control System, Thrust Vector Control, Auxiliary Power Unit, and Hydraulic Systems. The ESAS originally recommended a CEV to be launched atop a four-segment Space Shuttle Main Engine (SSME) CLV, utilizing an RS-25 engine-powered upper stage. However, Agency decisions to utilize fewer CLV development steps to lunar missions, reduce the overall risk for the lunar program, and provide a more balanced engine production rate requirement prompted engineers to switch to a five-segment design with a single Saturn-derived J-2X engine. This approach provides for single upper stage engine development for the CLV and an Earth Departure Stage, single Reusable Solid Rocket Booster (RSRB) development for the CLV and a Cargo Launch Vehicle, and single core SSME development. While the RSRB design has changed since the CLV Project's inception, the USE design has remained essentially a clean-sheet approach. Although a clean-sheet upper stage design inherently carries more risk than a modified design, it does offer many advantages: a design for increased reliability; built-in extensibility to allow for commonality/growth without major redesign; and incorporation of state-of-the-art materials, hardware, and design, fabrication, and test techniques and processes to facilitate a potentially better, more reliable system. Because consideration was given in the ESAS to both clean-sheet and modified USE designs, this paper will highlight the advantages and disadvantages of both approaches and provide a detailed discussion of trades/selections made that led to the final upper stage configuration.

Davis, Daniel J.↗

NASA NTRS2020

Lunar Transient Accelerations White Paper

Recently, the United States announced a plan to return astronauts to the moon by 2024 [8]. Lunar landing (and subsequent Mars landing) architecture was not considered when the current NASA standards and vehicle design requirements for crew injury risk were developed. Therefore a gap exists in protecting the crew in planetary landing scenarios. One of the interesting aspects of this design reference mission (DRM)is the consideration of having the crew stand during dynamic phases of flight. Although this approach was contemplated for the Apollo Lunar Module, current NASA standards do not address design solutions that allow the crew to stand. Currently, NASA uses several tools and associated limits to mitigate crew injury because of dynamic loads. Some of these tools are the Brinkley Dynamic Response Criterion (BDRC) model and Hybrid III Anthropomorphic Test Devices (ATDs) [10]; and these have several limitations for assessing spaceflight loading environments, as well as specific underlying assumptions that may not be applicable in planetary landing vehicles. The BDRC is a simple lumped mass parameter model developed by the U.S. military, and has been used primarily to evaluate injury risk associated with aircraft ejection systems. The model evaluates seat accelerations in each axis to determine injury risk. Because the model treats the human-seat-restraint system as a single system, it is contingent on a restraint system and seat with similar characteristics of the original test data underlying the model. In particular, the model requires a rigid seat with a minimum natural frequency of 15Hz, minimal seat pan padding, side supports, and multipoint harness. The BDRC model uses undamped natural frequency and damping coefficients based on these requirements and any deviations may render the model injury predictions void. In lunar landing, one expects that a minimal or even no seat with minimal restraints will be employed. In this case, the original model parameters are likely to not be applicable. For capsule-based spacecraft returning crew to Earth, the Hybrid III ATD in various sizes also is used to supplement the BDRC. This analytical tool was added to address limitations in the BDRC related to spacecraft landings while wearing a pressure garment and helmet. Although the Hybrid III ATD has additional measurement capability; head, neck,and lumbar spine responses were the only metrics included because of the limitations imposed by the model.Lunar landing acceleration limits must assume the crew is standing during landing, an orientation for which we have limited data.Although the Apollo missions did employ a standing orientation for the crew, much of the data is lost. Therefore data from othersources havebeen examined to inform lunar landing acceleration limits.

Jeffrey T Somers↗

NASA NTRSDate not supplied

Optimized Trajectory Correction Burn Placement for NRHO Orbit Maintenance

NASA's future Artemis missions plan to utilize a near rectilinear halo orbit (NRHO) in the lunar vicinity to facilitate access to the lunar surface and place other critical assets to support human exploration. This exploration architecture requires a vehicle to remain in the NRHO for long periods of time ranging from several days, to weeks, to months, and even years. Consequently, periodic orbit maintenance burns become essential to ensure the spacecraft follows the desired reference trajectory in an efficient yet effective manner despite crew activity, navigation uncertainty, maneuver execution errors, disturbance accelerations, orbit insertion dispersions, and other system limitations. This work introduces a targeting algorithm that can be utilized to analyze a variety of targeting constraints and parameters that maximizes overall performance. Techniques associated with robust trajectory optimization are used to identify the optimized number and placement for NRHO trajectory correction (NTC) burns that accounts for the mission schedule, both a primary and backup navigation system, targeting strategies and burn plan configurations, vehicle venting, thruster selection, and integrated GN\&C performance. A notional scenario extracted from the NASA Artemis III mission is used to motivate and demonstrate these concepts and performance results.

Linear Covariance Analysis↗

DOE OSTI2025

An Evaluation of Representation Learning Methods in Particle Physics Foundation Models

We present a systematic evaluation of representation learning objectives for particle physics within a unified framework. Our study employs a shared transformer-based particle-cloud encoder with standardized preprocessing, matched sampling, and a consistent evaluation protocol on a jet classification dataset. We compare contrastive (supervised and self-supervised), masked particle modeling, and generative reconstruction objectives under a common training regimen. In addition, we introduce targeted supervised architectural modifications that achieve state-of-the-art performance on benchmark evaluations. This controlled comparison isolates the contributions of the learning objective, highlights their respective strengths and limitations, and provides reproducible baselines. We position this work as a reference point for the future development of foundation models in particle physics, enabling more transparent and robust progress across the community.

Chen, Michael [Caltech]↗

NASA NTRS2017

In-Situ Navigation and Timing Services for the Human Mars Landing Site Part 1: System Concept

In [1] and [2], we introduce a new geometric trilateration method that simultaneously performs absolute positioning and relative positioning. The relative position is derived from a “differencing” function of two raw-range measurements between a known reference point and of the target from a navigation satellite, thereby eliminating most of the common errors like atmospheric delays, ephemeris errors, and instrument delays in real-time. In the Mars environment this “error-cancellation” function greatly reduces the need to perform extensive orbit determination (OD) of the navigation satellites like the Earth’s GPS, and only requires occasional tracks from the Earth’s large-aperture deep space antennas to perform OD’s. Leveraging on this scheme, we propose a low-cost, low-maintenance regional navigation satellite system architecture that provides in-situ navigation and timing services for robotic and human missions in the vicinity of a Mars landing site. This architecture is built upon the proposed Mars relay network infrastructure, and a number of notional Mars orbiting and surface missions in the human exploration era of Mars. We assume two areostationary Mars relay orbiters that have continuous line-of-sight visibility with the Mars landing site, a Deep Space Habitat (DSH) in an inclined 48-hour circular orbit, and a surface communication lander that could serve as the reference point. These orbiting and surface infrastructure elements broadcast GPS-like ranging signals and other ephemeris information to the mission users. With one or more additional orbiters in areosynchronous orbits that trace around a figure-8 path, a regional navigation satellite system can be realized that provides in-situ course absolute localization and precision relative localization and timing services to the users in the vicinity of a Mars landing site. This paper describes the system concept of the proposed Mars regional navigation satellite system.

Lee, Charles↗

NASA NTRS2019

Advancing the Standards for Unmanned Air System Communications, Navigation and Surveillance

Under NASA program NNA16BD84C, new architectures were identified and developed for supporting reliable and secure Communications, Navigation and Surveillance (CNS) needs for Unmanned Air Systems (UAS) operating in both controlled and uncontrolled airspace. An analysis of architectures for the two categories of airspace and an implementation technology readiness analysis were performed. These studies produced NASA reports that have been made available in the public domain and have been briefed in previous conferences. We now consider how the products of the study are influencing emerging directions in the aviation standards communities. The International Civil Aviation Organization (ICAO) Communications Panel (CP), Working Group I (WG-I) is currently developing a communications network architecture known as the Aeronautical Telecommunications Network with Internet Protocol Services (ATN/IPS). The target use case for this service is secure and reliable Air Traffic Management (ATM) for manned aircraft operating in controlled airspace. However, the work is more and more also considering the emerging class of airspace users known as Remotely Piloted Aircraft Systems (RPAS), which refers to certain UAS classes. In addition, two Special Committees (SCs) in the Radio Technical Commission for Aeronautics (RTCA) are developing Minimum Aviation System Performance Standards (MASPS) and Minimum Operational Performance Standards (MOPS) for UAS. RTCA SC-223 is investigating an Internet Protocol Suite (IPS) and AeroMACS aviation data link for interoperable (INTEROP) UAS communications. Meanwhile, RTCA SC-228 is working to develop Detect And Avoid (DAA) equipment and a Command and Control (C2) Data Link MOPS establishing LBand and C-Band solutions. These RTCA Special Committees along with ICAO CP WG/I are therefore overlapping in terms of the Communication, Navigation and Surveillance (CNS) alternatives they are seeking to provide for an integrated manned- and unmanned air traffic management service as well as remote pilot command and control. This paper presents UAS CNS architecture concepts developed under the NASA program that apply to all three of the aforementioned committees. It discusses the similarities and differences in the problem spaces under consideration in each committee, and considers the application of a common set of CNS alternatives that can be widely applied. As the works of these committees progress, it is clear that the overlap will need to be addressed to ensure a consistent and safe framework for worldwide aviation. In this study, we discuss similarities and differences in the various operational models and show how the CNS architectures developed under the NASA program apply.

Ponchak, Denise S.↗

NASA NTRS2006

Next Generation System and Software Architectures: Challenges from Future NASA Exploration Missions

The four key objective properties of a system that are required of it in order for it to qualify as "autonomic" are now well-accepted-self-configuring, self-healing, self-protecting, and self-optimizing- together with the attribute properties-viz. self-aware, environment-aware, self-monitoring and self- adjusting. This paper describes the need for next generation system software architectures, where components are agents, rather than objects masquerading as agents, and where support is provided for self-* properties (both existing self-chop and emerging self-* properties). These are discussed as exhibited in NASA missions, and in particular with reference to a NASA concept mission, ANTS, which is illustrative of future NASA exploration missions based on the technology of intelligent swarms.

Sterritt, Roy↗

NASA NTRS2013

Space Communication and Navigation Testbed Communications Technology for Exploration

NASA developed and launched an experimental flight payload (referred to as the Space Communication and Navigation Test Bed) to investigate software defined radio, networking, and navigation technologies, operationally in the space environment. The payload consists of three software defined radios each compliant to NASAs Space Telecommunications Radio System Architecture, a common software interface description standard for software defined radios. The software defined radios are new technology developed by NASA and industry partners. The payload is externally mounted to the International Space Station truss and available to NASA, industry, and university partners to conduct experiments representative of future mission capability. Experiment operations include in-flight reconfiguration of the SDR waveform functions and payload networking software. The flight system communicates with NASAs orbiting satellite relay network, the Tracking, Data Relay Satellite System at both S-band and Ka-band and to any Earth-based compatible S-band ground station.

Reinhart, Richard↗

NASA NTRS2014

Overview of the Contributing Factor Map and How it can Support your Research

The Contributing Factor Map (CFM) is a visual representation of a taxonomy of factors influencing human health and performance in space. This presentation will give an overview of its development and its structure. It will describe various uses of the CFM that can support researchers working within the Human Research Program (HRP) Architecture of Evidence-Risk-Gap-Task-Deliverable. For example, during the Risk phase, the CFM can be used as a "menu" to help formulate a qualitative model of the factors contributing to specific consequences of concern. It provides a reference set of factors from across the operational, vehicle design, and human domains that otherwise might not be considered if approaching a risk from a specific domain perspective. Using the CFM as a reference can increase awareness of potential cross-disciplinary collaborations for overall risk mitigation. The CFM can also be used as a framework for identifying gaps in knowledge about a risk. This identification can support the subsequent development of gaps and tasks comprising the research plan aimed at risk mitigation. Examples of these types of applications of the CFM will be discussed and information on the support available to researchers in using it will be provided.

Mindock, Jennifer A.↗

NASA NTRS2014

Space Launch System Ascent Flight Control Design

A robust and flexible autopilot architecture for NASA's Space Launch System (SLS) family of launch vehicles is presented. The SLS configurations represent a potentially significant increase in complexity and performance capability when compared with other manned launch vehicles. It was recognized early in the program that a new, generalized autopilot design should be formulated to fulfill the needs of this new space launch architecture. The present design concept is intended to leverage existing NASA and industry launch vehicle design experience and maintain the extensibility and modularity necessary to accommodate multiple vehicle configurations while relying on proven and flight-tested control design principles for large boost vehicles. The SLS flight control architecture combines a digital three-axis autopilot with traditional bending filters to support robust active or passive stabilization of the vehicle's bending and sloshing dynamics using optimally blended measurements from multiple rate gyros on the vehicle structure. The algorithm also relies on a pseudo-optimal control allocation scheme to maximize the performance capability of multiple vectored engines while accommodating throttling and engine failure contingencies in real time with negligible impact to stability characteristics. The architecture supports active in-flight disturbance compensation through the use of nonlinear observers driven by acceleration measurements. Envelope expansion and robustness enhancement is obtained through the use of a multiplicative forward gain modulation law based upon a simple model reference adaptive control scheme.

Orr, Jeb S.↗

NASA NTRSDate not supplied

Artemis Navigation Architecture: Early Capabilities and Long Term Evolvability and Evolution

With the awarding of multiple contracts within the Artemis program and building on the success of Artemis I, NASA is investing in and demonstrating the vehicle capabilities necessary for a return to human crewed Lunar Missions. To support activities on the lunar surface, NASA is also assessing architecture options and approaches to enable high precision in-situ navigation within the lunar sphere of influence. These capabilities build on decades of research and advancements within the field, building and evolving the techniques used during Apollo. To support inter-operability and broad application within its elements, NASA conducted a trade on Orbital and Surface Lunar Architecture for PNT. Time-defined mission requirements were captured across elements to inform a phased approach and deployment of needed capability. The architecture must also address unique aspects of the South Pole lunar environments, specifically in terms of harsh lighting and hazardous terrain. To inform the study, documentation of primary users, operational concepts of operations, driving scenarios, and mission needs were used to define performance constraints and phasing. Multiple technologies were assessed in terms of maturity, applicability, and performance to meet the primary user needs forecast. The results of this study support the utilization of in-situ orbital infrastructure to provide a back-bone for navigation and emphasize the need for a common Lunar Reference System and Lunar Time Reference. This deployment can ensure compatibility and enable a high-accuracy in-situ capability. This provides further justification for the capabilities being invested in and deployed by NASA and other international agencies. In addition to including advancements in terrestrial surface navigation, NASA is also applying lessons learned and innovation in the contractual approach to the individual elements by means of a services-based contract mechanism. This impacts the navigation architecture heavily in terms of government and provider roles, in terms of levels of implementation, interoperability, and verification. These distinctions in roles provide constraints to the architecture approach in terms of implementation and integration and will be discussed. The development, use, and mandate of interoperability standards are being deployed to support cross-element compatibility. This paper will provide a summary of the NASA Lunar Navigation needs across its various elements and the proposed deployment of an integrated navigation architecture to support early mission needs with inherent extensibility towards the future.

Evan Anzalone↗

NASA NTRS2010

Control Activity in Support of NASA Turbine Based Combined Cycle (TBCC) Research

Control research for a Turbine Based Combined Cycle (TBCC) propulsion system is the current focus of the Hypersonic Guidance, Navigation, and Control (GN&C) discipline team. The ongoing work at the NASA Glenn Research Center (GRC) supports the Hypersonic GN&C effort in developing tools to aid the design of control algorithms to manage a TBCC airbreathing propulsion system during a critical operating period. The critical operating period being addressed in this paper is the span when the propulsion system transitions from one cycle to another, referred to as mode transition. One such tool, that is a basic need for control system design activities, is computational models (hereto forth referred to as models) of the propulsion system. The models of interest for designing and testing controllers are Control Development Models (CDMs) and Control Validation Models (CVMs). CDMs and CVMs are needed for each of the following propulsion system elements: inlet, turbine engine, ram/scram dual-mode combustor, and nozzle. This paper presents an overall architecture for a TBCC propulsion system model that includes all of the propulsion system elements. Efforts are under way, focusing on one of the propulsion system elements, to develop CDMs and CVMs for a TBCC propulsion system inlet. The TBCC inlet aerodynamic design being modeled is that of the Combined-Cycle Engine (CCE) Testbed. The CCE Testbed is a large-scale model of an aerodynamic design that was verified in a small-scale screening experiment. The modeling approach includes employing existing state-of-the-art simulation codes, developing new dynamic simulations, and performing system identification experiments on the hardware in the NASA GRC 10 by10-Foot Supersonic Wind Tunnel. The developed CDMs and CVMs will be available for control studies prior to hardware buildup. The system identification experiments on the CCE Testbed will characterize the necessary dynamics to be represented in CDMs for control design. These system identification models will also be the reference models to validate the CDM and CVM models. Validated models will give value to the tools used to develop the models.

Stueber, Thomas J.↗

NASA NTRS2022

Gender Diversity in Heliophysics

Science is conducted by people. When those people do not feel safe in their workplace, they will struggle to produce quality science. The American scientific community has traditionally been dominated by cisgender white men–cisgender meaning that their gender aligns with the one assigned to them at birth. Individuals who are not part of this dominant demographic group have historically been excluded from scientific debate. However, the demographic landscape is changing rapidly [e.g., Jones (2022)], and organizations must ensure early career scientists of all identities feel accepted so they can achieve their goals in the field. Heliophysics describes the confluence and interaction of historically delineated scientific disciplines, including plasma, solar, and space physics. The scientific architecture of our field is founded on collaboration between people with diverse interests, backgrounds, skill sets, and ways of approaching problems. It should follow that the cohort of heliophysicists is at least as diverse as our research problems. A framing often referred to as “the business case” for diversity holds that perspectives different than our own enrich the ways in which we solve problems and communicates the positive outcomes for diverse working groups Starck et al. (2021). However, this rationale is insufficient in scope and uncompassionate in motivation; the safety of marginalized individuals is just as important as the achievements of a group. From the expectations that marginalized people outperform in order to prove themselves to the tokenization of their inclusion in an otherwise normative space, the “business case” for diversity is often harmful to historically marginalized individuals Haacker et al. (2022). The primary motivation for a diverse constituency of heliophysicists ought to be equity. Only by accepting the authentic selves of our fellow heliophysicists can we create an environment in which they have the mental and emotional safety necessary to do their best work. This white paper focuses on a particular axis of identity which the authors believe lacks visibility within heliophysics: gender expansion. It begins with definitions, explains the current landscape, and suggests actions toward a better future. The authors seek to shed light on these issues so that we can work together as a community to create a more inclusive, safe, and welcoming space for people of all identities.

M. Kenny↗

NASA NTRS1978

Suggested architecture for a specialized fluid dynamics computer

Future flow simulations in 3-D will require computers with extremely large main memories and an advantageous ratio between computer cost and arithmetic speed. Since random access memories are very expensive, a pipeline design is proposed which allows the use of much cheaper sequential devices without any sacrifice in speed for vector references (even with arbitrary spacing between successive elements). Also scalar arithmetic can be performed efficiently. The comparatively low speed of the proposed machine (about 10 to the 7th power operations per second) would be offset by a very low price per unit, making mass production possible.

Fornberg, B.↗

DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗

DOE OSTI2026

Analog-to-digital converter based on voltage-controlled superconducting devices

The increasing demand for cryogenic electronics in superconducting and quantum computing systems calls for ultra-energy-efficient data conversion architectures that remain functional at deep cryogenic temperatures. Here, in this work, we present the first design of a voltage-controlled superconducting flash analog-to-digital converter (ADC) based on a voltage-controlled quantum-enhanced Josephson junction field-effect transistor (JJFET). Exploiting its strong gate tunability and transistor-like behavior, the JJFET offers a scalable alternative to conventional current-controlled superconducting devices while aligning naturally with CMOS-style design methodologies. Building on our previously developed Verilog-A compact model calibrated to experimental data, we design and simulate a three-bit JJFET-based flash ADC targeted for integration within cryogenic control and readout circuitry in quantum computing. The core comparator block is realized through careful bias current selection and augmented with a three-terminal nanocryotron to precisely define reference voltages. Cascaded JJFET comparators ensure robust voltage gain, cascadability, and logic-level restoration across stages. Simulation results demonstrate accurate quantization behavior with ultra-low power dissipation, underscoring the feasibility of voltage-driven superconducting mixed-signal circuits. This work establishes a critical step toward unifying superconducting logic and data conversion, paving the way for scalable cryogenic architectures in quantum–classical co-processors, low-power artificial intelligence accelerators, and next-generation energy-constrained computing platforms.

Analog-to-digital converter↗

DOE OSTI2026

Deep learning for time series forecasting: a survey of recent advances

Time series forecasting plays a critical role in numerous real-world applications, such as finance, healthcare, transportation, and scientific computing. In recent years, deep learning has become a powerful tool for modeling complex temporal patterns and improving forecasting accuracy. This survey provides an overview of recent deep learning approaches for time series forecasting, involving various architectures including RNNs, CNNs, GNNs, transformers, large language models, MLP-based models, and diffusion models. We first identify key challenges in the field, such as temporal dependency, efficiency, and cross-variable dependency, which drive the development of forecasting techniques. Then, the general advantages and limitations of each architecture are discussed to contextualize their adaptation in time series forecasting. Furthermore, we highlight promising design trends like multi-scale modeling, decomposition, and frequency-domain techniques, which are shaping the future of the field. This paper serves as a compact reference for researchers and practitioners seeking to understand the current landscape and future trajectory of deep learning in time series forecasting.

97 MATHEMATICS AND COMPUTING↗