Search NASA⌕ Search

SEARCH · Search NASA

Results for “circuit model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml

We present the implementation of binary and ternary neural networks in the hls4ml library, designed to automatically convert deep neural network models to digital circuits with FPGA firmware. Starting from benchmark models trained with floating point precision, we investigate different strategies to reduce the network's resource consumption by reducing the numerical precision of the network parameters to binary or ternary. We discuss the trade-off between model accuracy and resource consumption. In addition, we show how to balance between latency and accuracy by retaining full precision on a selected subset of network components. As an example, we consider two multiclass classification tasks: handwritten digit recognition with the MNIST data set and jet identification with simulated proton-proton collisions at the CERN Large Hadron Collider. The binary and ternary implementation has similar performance to the higher precision implementation while using drastically fewer FPGA resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Modeling the Impacts of Material Properties on Oscillatory Neuron Behavior

In this study, neuromorphic computing, which mimics the functions of biological brains, offers improvements in both latency and energy efficiency over typical von Neumann computing architectures. Spiking neural networks can be especially power-efficient because they encode information temporally and can use more sparse electrical inputs. Here, we study the design of volatile memristors (variable resistors with memory) for neuronal devices, with particular consideration toward the feasibility of all-on-chip oscillation using built-in capacitance. We use circuit simulations to model the behavior of oscillator neurons with a range of realistic material properties. We find that energy inputs increase with insulating-phase resistivity, thermal conductivity, and device aspect ratio. However, we also find that the minimum capacitance needed for oscillation decreases with increasing insulating-phase resistivity, which opposes the constraints for power efficiency. Based on published data on NbO 2 , VO 2 , and EuNiO 3 , we find that existing materials can be engineered for all-on-chip spiking using their parasitic capacitance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Model Reduction by Generalized Falk Method for Efficient Field-Circuit Simulations

The Generalized Falk Method (GFM) for coordinate transformation, together with two model-reduction strategies based on this method, are presented for efficient coupled field-circuit simulations. Each model-reduction strategy is based on a decision to retain specific linearly-independent vectors, called trial vectors, to construct a vector basis for coordinate transformation. The reduced-order models are guaranteed to be stable and passive since the GFM is a congruence transformation of originally symmetric positive definite systems. We also show that, unlike the Pad´e-via-Lanczos (PVL) method, the GFM does not generate unstable positive poles while reducing the order of circuit problems. Further, the proposed GFM is also faster when compared to methods of the type Lanczos (or Krylov) that are already widely used in circuit simulations for electrothermal and electromagnetic problems. The concept of response participation factors is introduced for the selection of the trial vectors in the proposed model-reduction methods. Further, we present methods to develop simple equivalent circuit networks for the field component of the overall field-circuit system. The implementation of these equivalent circuit networks in circuit simulators is discussed. With the proposed model-reduction strategies, significant improvement on the efficiency of the generalized Falk method is illustrated for coupled field-circuit problems.

42 ENGINEERING↗
DOE OSTI2020

Genetic circuit design automation for yeast

Cells can be programmed to monitor and react to their environment using genetic circuits. Design automation software maps a desired circuit function to a DNA sequence, a process that requires units of gene regulation (gates) that are simple to connect and behave predictably. This poses a challenge for eukaryotes due to their complex mechanisms of transcription and translation. To this end, we have developed gates for yeast (Saccharomyces cerevisiae) that are connected using RNA polymerase flux as the signal carrier and are insulated from each other and host regulation. They are based on minimal constitutive promoters (~120 base pairs), for which rules are developed to insert operators for DNA-binding proteins. Using this approach, in this work we constructed nine NOT/NOR gates with nearly identical response functions and 400-fold dynamic range. In circuits, they are transcriptionally insulated from each other by placing ribozymes downstream of terminators to block nuclear export of messenger RNAs resulting from RNA polymerase readthrough. Based on these gates, Cello 2.0 was used to build circuits with up to 11 regulatory proteins. A simple dynamic model predicts the circuit response over days. Genetic circuit design automation for eukaryotes simplifies the construction of regulatory networks as part of cellular engineering projects, whether it be to stage processes during bioproduction, serve as environmental sentinels or guide living therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Slow thermalization and subdiffusion in $U$(1) conserving Floquet random circuits

Random quantum circuits are paradigmatic models of minimally structured and analytically tractable chaotic dynamics. We study a family of Floquet unitary circuits with Haar random U(1) charge conserving dynamics; the minimal such model has nearest-neighbor gates acting on spin-1/2 qubits, and a single layer of even/odd gates repeated periodically in time. We find that this minimal model is not robustly thermalizing at numerically accessible system sizes, and displays slow subdiffusive dynamics for long times. We map out the thermalization dynamics in a broader parameter space of charge conserving circuits, and understand the origin of the slow dynamics in terms of proximate localized and integrable regimes in parameter space. In contrast, we find that small extensions to the minimal model are sufficient to achieve robust thermalization; these include (i) increasing the interaction range to three-site gates, (ii) increasing the local Hilbert space dimension by appending an additional unconstrained qubit to the conserved charge on each site, or (iii) using a larger Floquet period comprised of two independent layers of gates. Furthermore, our results should inform future studies of charge conserving circuits, which are relevant for a wide range of topical theoretical questions.

1-dimensional spin chains↗
DOE OSTI2026

Universal monitored dynamics in multimode bosonic systems

We propose a route to study monitored many-body dynamics in multimode bosonic systems using circuit quantum electrodynamics. In this experimental setting, we construct several bosonic models comprising brickwork circuits built from beam-splitter gates, local parity measurements, and optional on-site Hubbard interactions, and diagnose their monitored dynamics via ancilla purification and a learnability-based probe. Under parity measurements, generic gate sets exhibit behavior that is largely consistent with a conventional measurement-induced phase transition, while a special class of beam-splitter circuits shows an apparent critical-like high-measurement regime in which purification times scale linearly with system size. We show that for realistic noise, gate, and measurement rates, these signatures are observable with near-term circuit QED hardware.

Patel, Shivam [Rutgers U., Piscataway]↗
DOE OSTI2021

Status of EM Pump Modeling Capability for VTR

SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. Most recently, SAS4A/SASSYS-1 has been selected as the safety analysis software for the Versatile Test Reactor (VTR), a new materials testing Sodium Fast Reactor (SFR) to be built by the Department of Energy. In order to support analysis of the VTR, which will utilize ElectroMagnetic (EM) pumps as the primary coolant pumps, the development of new EM pump modeling capabilities has been initiated for SAS4/SASSYS-1. The new physics-based EM pump model captures systems-level transient performance based on equivalent circuit theory and is highly flexible to model a wide range of electromagnetic pumps of the three-phase linear induction type subject to changes in power supply and plant conditions. Within the equivalent circuit framework, two sub-models are developed to provide options for analysts both with and without a detailed geometric characterization of their pump such that minimal information is required to achieve a realistic working model, but specific details of a particular pump design may be captured if sufficient information is provided. In addition, heat generated from pump operation and its transport through the plant system can be modeled to better capture the behavior of certain transients. This paper will outline the model and derive the governing equations of the new EM pump model. An initial comparison between the simple EM pump model and experimental data is made. This comparison shows that the equivalent circuit model can capture pump performance, with greater accuracy near the rated conditions. In order to demonstrate the transient behavior of the new model, a simple transient with an EM pump replacing the centrifugal pumps in the Advanced Burner Test Reactor is included.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Status of EM Pump Modeling Capability for VTR

SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. Most recently, SAS4A/SASSYS-1 has been selected as the safety analysis software for the Versatile Test Reactor (VTR), a new materials testing Sodium Fast Reactor (SFR) to be built by the Department of Energy. In order to support analysis of the VTR, which will utilize ElectroMagnetic (EM) pumps as the primary coolant pumps, the development of new EM pump modeling capabilities has been initiated for SAS4/SASSYS-1. The new physics-based EM pump model captures systems-level transient performance based on equivalent circuit theory and is highly flexible to model a wide range of electromagnetic pumps of the three-phase linear induction type subject to changes in power supply and plant conditions. Within the equivalent circuit framework, two sub-models are developed to provide options for analysts both with and without a detailed geometric characterization of their pump such that minimal information is required to achieve a realistic working model, but specific details of a particular pump design may be captured if sufficient information is provided. In addition, heat generated from pump operation and its transport through the plant system can be modeled to better capture the behavior of certain transients. This paper will outline the model and derive the governing equations of the new EM pump model. An initial comparison between the simple EM pump model and experimental data is made. This comparison shows that the equivalent circuit model can capture pump performance, with greater accuracy near the rated conditions. In order to demonstrate the transient behavior of the new model, a simple transient with an EM pump replacing the centrifugal pumps in the Advanced Burner Test Reactor is included.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Advancing wildlife connectivity in land use planning: a case study with four-toed salamanders

Stable habitat connections that wildlife can safely traverse are essential to biodiversity conservation and healthy ecosystems. We developed high-resolution landscape connectivity models to predict resistance to movement by a threatened wetland-obligate amphibian, the four-toed salamander ( Hemidactylium scutatum ), and identified priority management areas on the 13,000-ha Department of Energy Oak Ridge Reservation (ORR) from 2019 to 2022. We developed a resistance surface based on aerial light detection and ranging data (LiDAR), >30 years of field-based mapping of forest, hydrologic, and geologic features, and contemporary population surveys, alongside derived predictors at <1-m resolution. We then modeled predicted movement corridors using a circuit theory-based modeling approach. We worked closely with land management and natural resources personnel to integrate ecological modeling with broader land use priorities, monetary costs, and feasibility. We identified important terrestrial and aquatic areas on ORR and simulated management scenarios to promote stable connections for four-toed salamanders. This approach allowed us to narrow down a list of 438 potential habitat manipulation sites to 10 sites where open-bottomed culverts and buffers could be implemented. This smaller-scale restoration approach produced a similar increase in landscape connectivity while costing <20% of a larger-scale approach based on barrier removal. We successfully identified feasible, cost-effective management strategies that integrated knowledge from a variety of sources. In conclusion, we offer a strategy that permitted integration of wildlife management goals into infrastructure upgrades wherein wildlife was not an initial consideration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Probe measurements of electric field and electron density fluctuations at megahertz frequencies using in-shaft miniature circuits

In this work, a four-tip electrostatic probe is constructed to measure high-frequency (0.1–10 MHz) fluctuations in both the electric field (one component) and electron density in a laboratory plasma. This probe also provides data for the local electron temperature and density. Circuits for high-frequency measurements are fabricated on two miniature boards, which are embedded in the probe shaft, near the tips to minimize the pickup of common-mode signals. The amplitude and phase response of two circuits to sinusoidal test signals are measured and compared with results from modeling. For both circuits, the phase shift between input and output signals is relatively small (<30°). The performance of the probe is verified in a high-density (~10 13 cm –3 ) and low-temperature (≲10 eV) plasma. The probe successfully measures high-frequency (~2 MHz) fluctuations in the electric field and density, which are associated with lower hybrid drift waves. This probe can provide information on the wave-associated anomalous drag, which can be compared with the classical resistivity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

An Investigation into High Voltage Spiral Generators Utilizing Thyristor Input Switches

High voltage nanosecond pulses are widely used in scientific research, but their wider adoption in industry requires compact, cost effective and easy to use generators to be developed. This paper presents modelling and experimental investigations into one method of producing such pulses – a spiral generator with a solid-state, thyristor-based input switch. It includes how the pulses are formed within the spiral, why a high speed input switch is required, how the geometry of the spiral dictates its output characteristics, and the effects of different loads. Using thyristors, often connected in series to increase the operating voltage of the spiral, enables the spiral generators to have low jitter, high repetition rate, and long lifetime. Modelling of the circuit used a combination of telegraph equations to account for the wave propagation along the spiral and a lumped circuit exchanging charge between the spiral, the input switch, and the load. The model is verified by detailed experimental results with the relative error being < 10% in most cases. Here, the output voltage pulse was often observed to have an initial peak of much lower magnitude than the subsequent peak(s) – which can only be fully explained by considering wave propagation effects. Lower input switch inductance, shorter switching time, larger mean diameter of the spiral, and increasing the width of the copper tape that makes up the spiral can all increase the voltage multiplication efficiency. Though increasing the number of turns that make up the spiral can increase the output voltage, it can also lower the multiplication efficiency. By understanding the effects of different geometries the spiral can be optimized to drive different loads - three applications of such spiral generators are then presented: pulses with 10 kV amplitude and 10 kHz repetition rate for driving DBD plasma, pulses with amplitude of 10 kV and 10 kV/ns rising rate for triggering of advanced solid state switches, and pulses with -50 kV amplitude and 50 ns rising time for triggering high current gas switches through field distortion.1 Index Terms—spiral generator, nanosecond pulses, telegraph equations, series-connected thyristor module, pulse forming process

42 ENGINEERING↗
DOE OSTI2025

Surrogate Constructed Scalable Circuits ADAPT-VQE in the Schwinger model

Inspired by recent advancements of simulating periodic systems on quantum computers, we develop a new approach, (SC)$^2$-ADAPT-VQE, to further advance the simulation of these systems. Our approach extends the scalable circuits ADAPT-VQE framework, which builds an ansatz from a pool of coordinate-invariant operators defined for arbitrarily large, though not arbitrarily small, volumes. Our method uses a classically tractable ``Surrogate Constructed'' method to remove irrelevant operators from the pool, reducing the minimum size for which the scalable circuits are defined. Bringing together the scalable circuits and the surrogate constructed approaches forms the core of the (SC)$^2$ methodology. Our approach allows for a wider set of classical computations, on small volumes, which can be used for a more robust extrapolation protocol. While developed in the context of lattice models, the surrogate construction portion is applicable to a wide variety of problems where information about the relative importance of operators in the pool is available. As an example, we use it to compute properties of the Schwinger model - quantum electrodynamics for a single, massive fermion in $1+1$ dimensions - and show that our method can be used to accurately extrapolate to the continuum limit.

Gustafson, Erik [RIACS, Mtn. View] (ORCID:00000001↗
DOE OSTI2020

Classical versus quantum models in machine learning: insights from a finance application

Although several models have been proposed towards assisting machine learning (ML) tasks with quantum computers, a direct comparison of the expressive power and efficiency of classical versus quantum models for datasets originating from real-world applications is one of the key milestones towards a quantum ready era. Here, we take a first step towards addressing this challenge by performing a comparison of the widely used classical ML models known as restricted Boltzmann machines (RBMs), against a recently proposed quantum model, now known as quantum circuit Born machines (QCBMs). Both models address the same hard tasks in unsupervised generative modeling, with QCBMs exploiting the probabilistic nature of quantum mechanics and a candidate for near-term quantum computers, as experimentally demonstrated in three different quantum hardware architectures to date. To address the question of the performance of the quantum model on real-world classical data sets, we construct scenarios from a probabilistic version out of the well-known portfolio optimization problem in finance, by using time-series pricing data from asset subsets of the S&P500 stock market index. It is remarkable to find that, under the same number of resources in terms of parameters for both classical and quantum models, the quantum models seem to have superior performance on typical instances when compared with the canonical training of the RBMs. Our simulations are grounded on a hardware efficient realization of the QCBMs on ion-trap quantum computers, by using their native gate sets, and therefore readily implementable in near-term quantum devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Effective Field Theory of Random Quantum Circuits

Quantum circuits have been widely used as a platform to simulate generic quantum many-body systems. In particular, random quantum circuits provide a means to probe universal features of many-body quantum chaos and ergodicity. Some such features have already been experimentally demonstrated in noisy intermediate-scale quantum (NISQ) devices. On the theory side, properties of random quantum circuits have been studied on a case-by-case basis and for certain specific systems, and a hallmark of quantum chaos—universal Wigner–Dyson level statistics—has been derived. This work develops an effective field theory for a large class of random quantum circuits. The theory has the form of a replica sigma model and is similar to the low-energy approach to diffusion in disordered systems. The method is used to explicitly derive the universal random matrix behavior of a large family of random circuits. In particular, we rederive the Wigner–Dyson spectral statistics of the brickwork circuit model by Chan, De Luca, and Chalker [Phys. Rev. X 8, 041019 (2018)] and show within the same calculation that its various permutations and higher-dimensional generalizations preserve the universal level statistics. Finally, we use the replica sigma model framework to rederive the Weingarten calculus, which is a method of evaluating integrals of polynomials of matrix elements with respect to the Haar measure over compact groups and has many applications in the study of quantum circuits. The effective field theory derived here provides both a method to quantitatively characterize the quantum dynamics of random Floquet systems (e.g., calculating operator and entanglement spreading) and a path to understanding the general fundamental mechanism behind quantum chaos and thermalization in these systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Piezoelectric Energy Harvesting Gyroscopes: Comparative Modeling and Effectiveness

Given its versatility in drawing power from many sources in the natural world, piezoelectric energy harvesting (PEH) has become increasingly popular. However, its energy harvesting capacities could be enhanced further. Here, a mathematical model that accurately simulates the dynamic behavior and energy harvested can facilitate further improvements in the performance of piezoelectric devices. One of the goals of this study is to create a dependable reduced-order model of a multi-purpose gyroscope. This model will make it possible to compute the harvested voltage and electrical power in a semi-analytical manner. The harvested voltage is often modeled as an average value across the whole electrode surface in piezoelectric devices. We propose a model which provides practical insights toward optimizing the performance of the system by considering a spatially varying electric field across the electrode surface length. Our framework allows investigation of the limits of applicability of the modeling assumptions across a range of load resistances. The differential quadrature method (DQM) provides the basis for the suggested numerical solution. The model is also employed to examine energy harvesting under various resistance loads. The newly developed spatially varying model is evaluated for open- and closed-circuit conditions and is proved to be accurate for various values of load resistance that have not previously been considered. The results show that using a spatially varying model is more versatile when modeling the performance of the piezoelectric multifunctional energy harvester. The performance may be accurately captured by the model for load resistances ranging between 103 Ω and 108 Ω. At optimum load resistance and near 65 KHz, the maximum power output predicted by the spatially varying (SV) model is 1.3 mV, 1.5 mV for the open-circuit (OC) model, and 2.1 mV for the closed circuit (CE) model. At a high-load resistance, the SV and OC models all predict the maximum power output to be 1.9 mV while the CE model predicted the maximum voltage to be 3 mV.

42 ENGINEERING↗