The State of Software Development for Quantum Computers
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With growing energy supply concerns and rising costs, energy efficiency is a critical component of industrial energy resilience and competitiveness by directly reducing energy operating costs. Energy efficiency projects in manufacturing also yield valuable benefits to other key metrics, such as improved quality, reduced maintenance costs, improved safety, decreased pollution, and enhanced productivity. However, it is difficult to receive approval for energy efficiency projects, so implementation rates are low, even when meeting capital project payback period criteria. The inclusion and quantification of non-energy benefits (NEBs) in the decision-making process for energy efficiency projects can improve the overall financial payback period while demonstrating a positive impact on the firm's key performance metrics and business strategy. Despite their significant financial and strategic value, NEBs are rarely factored into decision-making due to lack of tools to effectively identify and quantify them. Therefore, a comprehensive and integrative approach is needed for the rapidly evolving energy landscape. To address these challenges, through funding from U.S. Department of Energy, our new assessment methodology integrates common continuous improvement six sigma concepts, such as the DMAIC process, and a protocol of guiding questions, into energy efficiency assessments to identify NEBs. We have also developed open-source software, JUSTIFI, to guide users through this process, data collection, and quantification. It is designed to be used concurrently with DOE energy system analysis software suite, MEASUR. Our methodology and tools inform energy assessors, firm engineering, decision makers, and workforce seeking to increase energy resilience and to maximize benefits aligned with performance metrics.
Multigrid methods are well suited to large massively parallel computer architectures because they are mathematically optimal and display good parallelization properties. Since current architecture trends are favoring regular compute patterns to achieve high performance, the ability to express structure has become much more important. The hypre software library provides high-performance multigrid preconditioners and solvers through conceptual interfaces, including a semistructured interface that describes matrices primarily in terms of stencils and logically structured grids. This paper presents a new semistructured algebraic multigrid (SSAMG) method built on this interface. The numerical convergence and performance of a CPU implementation of this method are evaluated for a set of semistructured problems. In conclusion, SSAMG achieves significantly better setup times than hypre’s unstructured AMG solvers and comparable convergence. In addition, the new method is capable of solving more complex problems than hypre’s structured solvers.
An overview of the basic techniques used to process Landsat images with a digital computer, and the VICAR image processing software developed at JPL and available to users through the NASA sponsored COSMIC computer program distribution center is presented. Examples of subjective processing performed to improve the information display for the human observer, such as contrast enhancement, pseudocolor display and band rationing, and of quantitative processing using mathematical models, such as classification based on multispectral signatures of different areas within a given scene and geometric transformation of imagery into standard mapping projections are given. Examples are illustrated by Landsat scenes of the Andes mountains and Altyn-Tagh fault zone in China before and after contrast enhancement and classification of land use in Portland, Oregon. The VICAR image processing software system which consists of a language translator that simplifies execution of image processing programs and provides a general purpose format so that imagery from a variety of sources can be processed by the same basic set of general applications programs is described.
diyepw allows for quick and easy generation of a set of EnergyPlus weather (EPW) files for a given location over a given historical period. The user can obtain weather files using an open-source, automated workflow by simply specifying the location of interest using the World Meteorological Organization weather station ID number, and specifying a year or set of years for which to generate EPW files. Building energy modelers can use these auto-generated weather files in building performance simulations to represent the actual observed weather conditions in the location(s) of interest, based on meteorological observations obtained from the National Oceanic and Atmospheric Administration's Integrated Surface Database. Because observed weather data are not available for every meteorological variable specified in the EPW format, diyepw starts with a widely-used set of typical meteorological year (TMY) files, using them as the template to generate new EPW files by substituting in the observed values of selected meteorological variables that are known to affect building energy performance. Its output is a weather file or group of weather files that conform to the data standards associated with the EPW format so they can be used with any building performance simulation software employing EnergyPlus as its simulation engine.
Climate modeling is an integral part of environmental research, from studying rare phenomena to predicting future climate trends. The need for more accurate models is only growing, but as climate modeling capabilities advance, existing workflows require optimization to recoup performance. A solution comes in the form of task parallelism, a novel programming capability that provides an opportunity for optimization at execution time by allowing tasks to be executed in parallel, reducing runtime significantly. Using Parsl, an intuitive and scalable parallel scripting library for Python, we implement task parallelism within support software to aid in the continuous advancement of climate modeling technology.
The MCNP unstructured mesh (UM) feature was implemented to allow MCNP to read in an Abaqus mesh geometry file, exported by external software packages such as Abaqus and CUBIT.
This document contains the official formulation that will be used for evaluation in Challenge 2 of the Grid Optimization (GO) Competition. Minor changes may occur within the formulation. Entrants will be notified when a new version is released. Changes are not expected to be of a significance that would cause a change in approach for the Entrants. This formulation builds upon the Challenge 1 formulation published in ARPA-E DE-FOA-0001952. Entrants will be judged based on the current official Challenge 2 formulation posted on the GO Competition website (this document, which is subject to change), not the formulation posted in DE-FOA-0001952. Entrants are permitted and encouraged to use any alternative problem formulation and modeling convention within their own software (such as convex relaxation, decoupled power flow formulations, current-voltage formulations, etc.) in an attempt to produce an exact or approximate solution to this particular mathematical program. However, the judging of all submitted approaches must conform to the official formulation presented here.
Secure environments face a steadily increasing threat from the introduction of scientific equipment that includes extensive software components. Devices such as powerful microscopes, 3d printers, programmable logic controllers, and many others, increase our capability and scientific output. Unfortunately, they now frequently include an entire computing stack with custom software bundled along with entire operating systems. Our ability to introspect and understand binary software is extremely limited, opening up the possibility of malicious third-parties including software that compromises our critical missions.
The Argonne Reactor Code (ARC) software suite [1-17] has been developed by Argonne researchers for fast reactor design and analysis since the 1970s. With the ARC software suite, a user can quickly build a model of a proposed or existing fast spectrum reactor and carry out fuel cycle, nominal thermal analysis and flow requirements, and assess, as is appropriate, whether the core design and constraint system yield an acceptable mechanical behavior. For transient reactor analysis with SAS4A [18], the ARC software suite can be used to generate reactivity coefficients and kinetics parameters at any modeled fuel cycle time point which forms part of the input to SAS4A. The ARC suite was consistently being developed until the 1990s and followed a software QA program which was an appropriate standard for the time. In the 1990s, the DOE funding to fast reactor research and development was all but eliminated and the ARC software was put into maintenance mode. In the early 2000s, the software quality assurance (SQA) program for ARC was still in place to define an official version, but by 2005 it all but was abandoned as there were insufficient staff to fill the work roles. Since 2005, there has been a considerable increase in research and design work on fast spectrum reactors. The ARC software as a whole has since been exported to many universities and commercial companies and ANL support has been given to the various projects over the years [19-23]. Further, MC 2 -3, PERSENT, and DASSH were all developed after 2005 without any adherence to a software standard. In recent time, the DOE VTR project [22] paid for verification work to be done on the ARC software as part of the goal of making it NQA-1 complaint. The VTR project was not considered the appropriate pathway to fund and maintain a SQA program for the ARC software and while software developments (DASSH) were made and several manuals were updated and software verification work was carried out, the ARC software is not NQA-1 compliant. More recently the Advanced Reactor Development Program (ARDP [23]) has funded the creation of manuals for some ARC utility programs and funded additional software verification work on DIF3D [6, 7] and MC 2 -3 [2-5] for the purpose of commercial grade dedication. Because of the VTR and ARDP projects, software verification work was completed on MC 2 -3 and DIF3D, and detailed reports were created for each piece of software, which discuss the inputs and outputs from the codes that are covered by the verification work and link various analytic, code-to-code, and hand calculation based verification work presented in the report with verification test problems provided with the software. This is a key part of the commercial grade dedication work and constitutes the bulk of the cost to get the ARC software to commercial grade. The ARC software suite is a valuable asset as a fast reactor design and analysis tool set that has been reasonably well verified and validated with various fast reactor benchmark problems and experiments over decades. Some or all of the ARC software suite has been utilized for designing the IFR [20], PGSFR [21], VTR [22], and Natrium [23] reactors and we can expect it to continue to be used for advanced fast reactor design and/or confirmatory calculation purposes in the future. Due to increased interest by commercial companies and regulatory bodies, it is becoming more important to make the ARC software suite complete and ready-to-use in terms of its SQA pedigree and commercial grade dedication needs. This report discusses the achievements made towards building a new SQA program for the ARC software and dealing with outstanding identified QA gaps.
The EvaluateFlux program is a post-processing utility program for DIF3D, specifically DIF3D-VARIANT which handles Cartesian and hexagonal geometries. The EvaluateFlux program was developed to allow users to obtain flux and power traverses through the geometry domain, and its initial purpose was to facilitate foil analysis by evaluating the flux solution from DIF3D-VARIANT and combining it with foil cross section data. The EvaluateFlux program can calculate the neutron flux, as well as the reaction rates, at any user provided evaluation point. It does this by identifying the spatial mesh associated with the evaluation point and then evaluates the polynomial based neutron flux moments stored in the NHFLUX file at that point. The output of EvaluateFlux varies depending on the input setup. The maximum output includes the neutron flux and microscopic and macroscopic reaction rates at each evaluation point. The purpose of this work is to verify the outputs of EvaluateFlux. Simple models that have hand calculatable results are first defined and used to verify the EvaluateFlux outputs. More complex cases are then added where a duplicate program of EvaluateFlux that uses PrintTables outputs of the binary files is used to verify the EvaluateFlux outputs. In those complex cases, hand calculations of selected evaluation points were also displayed to confirm the software verification. For all the tests done, the hand calculations agreed well with those calculated by EvaluateFlux. For the larger complex problems, the duplicate program that can process hundreds of evaluation points was able to identify that zero points within some meshes have large errors. This aspect was attributed to the truncation error on the input provided to the duplicate program and is not a concern for the accuracy of the EvaluateFlux software.
The rapid growth of photovoltaic (PV) deployment has increased reliance on software platforms for monitoring, workflow automation, diagnostics, and performance analytics. As these tools play a central role in asset management and operations and maintenance (O&M), greater transparency in methodologies, data handling, and validation practices benefits the broader PV ecosystem. To better understand current practices and identify opportunities for improved clarity and interoperability, 24 software providers contributed detailed responses through the PV O&M Analytics Collaborative (PVMAC) initiative, the first structured questionnaire of its kind in the industry, covering onboarding, interoperability, data quality, diagnostics, AI/ML, and other operational categories. These providers represent over 1.1 TW of solar assets under management. The analysis shows broad adoption of digital twins, AI/ML, and API integrations, but also highlights challenges in onboarding processes, inconsistent definitions and methodologies, variability in key performance indicator (KPI) calculations, and limited independent validation. Greater standardization, clearer documentation, and stronger validation frameworks could improve transparency, comparability, and trust across PV operations software platforms.
An analytical approach was developed to evaluate the electrodynamic interactions affecting a thin, bare metallic wire moving in the ionosphere. The wire's diameter was smaller than the Debye length; therefore, the plasma sheath around the wire was taken into account in computing inducing drag force and torque. Computer programs were prepared for the numerical evaluation of mathematical functions that were required to compute the distribution of the potential along the wire and of the current in the wire. Numerical calculations based on this software are shown.
In this memorandum, a set of processing strategies for automatic masking of phase calibration tones is outlined as implemented in the software package PIMA in the task Generate Phase Calibration Mask, or GEPM. The task relies on a robust procedure of cleaning phase calibration data before employing several mathematical strategies designed to selectively identify spurious signals from phase calibration tones. These strategies were derived as more rigorous implementations of heuristics traditionally used by analysts in manually identifying problematic phase calibration data. The task is intended to automate the process of generating a phase calibration mask and in so doing increase the speed and regularity of VLBI analysis. At the outset of the project, a series of goals were identified to evaluate the success of this mask generation. This included the development of an algorithm to identify and mask short-term (defined as less than 10 seconds in length) spurious signals affecting phase calibration data, the development of an algorithm to identify and mask phase calibration tones affected by constant radio-frequency interference, the implementation of a detection scheme for identifying large jumps in phase calibration phase caused by clock breaks, and finally a method of reporting phase calibration health metrics to the user. Processing of over 10 experiments has demonstrated that the final form of the task GEPM as detailed in this technical memorandum satisfies each of these conditions and satisfactorily performs the task of automatic phase calibration data masking, although the wide variety in quality and characteristics of phase calibration data makes a single solution to the problem quite difficult. A series of user inputs have therefore been defined to assist analysts in tailoring automatic masking to specific stations and phase calibration generators. The vast majority of applicable code was written in FORTRAN to increase execution speed and ease of interfacing with the existing code base in PIMA, but a wrapper function in Python was also written to allow for a simpler method of interacting with GEPM and inputting relevant parameters. In addition to this report, thorough documentation was added to the already existing repositories associated with PIMA as a whole.
There is a significant impact of dimensional errors in systems. Dimensional analysis is difficult due to the large size of systems. SA4U and Scalpel are practical programs which can have an impact beyond traditional software as they are able to perform precise dimensional analysis and repair C++ source code.
Communication networks in power systems are a major part of the smart grid paradigm. It enables and facilitates the automation of power grid operation as well as self-healing in contingencies. Such dependencies on communication networks, though, create a roam for cyber-threats. An adversary can launch an attack on the communication network, which in turn reflects on power grid operation. Attacks could be in the form of false data injection into system measurements, flooding the communication channels with unnecessary data, or intercepting messages. Using machine learning-based processing on data gathered from communication networks and the power grid is a promising solution for detecting cyber threats. In this paper, a co-simulation of cyber-security for cross-layer strategy is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection as well as identification of anomalies in the operation of the power grid. The framework is implemented on the IEEE 118-bus system. The system is constructed in Mininet to simulate a communication network and obtain data for analysis. A distributed three controller software-defined networking (SDN) framework is proposed that utilizes the Open Network Operating System (ONOS) cluster. According to the findings of our suggested architecture, it outperforms a single SDN controller framework by a factor of more than ten times the throughput. This provides for a higher flow of data throughout the network while decreasing congestion caused by a single controller’s processing restrictions. Furthermore, our CECD-AS approach outperforms state-of-the-art physics and machine learning-based techniques in terms of attack classification. The performance of the framework is investigated under various types of communication attacks.
Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.
Abstract We introduce the Weak-form Estimation of Nonlinear Dynamics (WENDy) method for estimating model parameters for non-linear systems of ODEs. Without relying on any numerical differential equation solvers, WENDy computes accurate estimates and is robust to large (biologically relevant) levels of measurement noise. For low dimensional systems with modest amounts of data, WENDy is competitive with conventional forward solver-based nonlinear least squares methods in terms of speed and accuracy. For both higher dimensional systems and stiff systems, WENDy is typically both faster (often by orders of magnitude) and more accurate than forward solver-based approaches. The core mathematical idea involves an efficient conversion of the strong form representation of a model to its weak form, and then solving a regression problem to perform parameter inference. The core statistical idea rests on the Errors-In-Variables framework, which necessitates the use of the iteratively reweighted least squares algorithm. Further improvements are obtained by using orthonormal test functions, created from a set of $$C^{\infty }$$ C ∞ bump functions of varying support sizes.We demonstrate the high robustness and computational efficiency by applying WENDy to estimate parameters in some common models from population biology, neuroscience, and biochemistry, including logistic growth, Lotka-Volterra, FitzHugh-Nagumo, Hindmarsh-Rose, and a Protein Transduction Benchmark model. Software and code for reproducing the examples is available at https://github.com/MathBioCU/WENDy .