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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Operator product expansion for radial lattice quantization of 3D ϕ 4 theory

At its critical point, the three-dimensional lattice Ising model is described by a conformal field theory (CFT), the 3D Ising CFT. Instead of carrying out simulations on Euclidean lattices, we use the quantum finite elements method to implement radially quantized critical ϕ 4 theory on simplicial lattices approaching R × S 2 . Computing the four-point function of identical scalars, we demonstrate the power of radial quantization by the accurate determination of the scaling dimensions Δ ε and Δ T as well as ratios of the operator product expansion coefficients f σ σ ε and f σ σ T of the first spin-0 and spin-2 primary operators ε and T of the 3D Ising CFT. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs

Here, we develop an end-to-end workflow for the training and implementation of co-designed neural networks (NNs) for efficient field-programmable gate array (FPGA) hardware. Our approach leverages Hessian-aware quantization of NNs, the Quantized Open Neural Network Exchange intermediate representation, and the hls4ml tool flow for transpiling NNs into FPGA firmware. This makes efficient NN implementations in hardware accessible to nonexperts in a single open sourced workflow that can be deployed for real-time machine-learning applications in a wide range of scientific and industrial settings. We demonstrate the workflow in a particle physics application involving trigger decisions that must operate at the 40-MHz collision rate of the CERN Large Hadron Collider (LHC). Given the high collision rate, all data processing must be implemented on FPGA hardware within the strict area and latency requirements. Based on these constraints, we implement an optimized mixed-precision NN classifier for high-momentum particle jets in simulated LHC proton-proton collisions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Numerical Simulation of Electron Magnetohydrodynamics with Landau-quantized Electrons in Magnetar Crusts

Abstract In magnetar crusts, magnetic fields are sufficiently strong to confine electrons into a small to moderate number of quantized Landau levels. This can have a dramatic effect on the crust's thermodynamic properties, generating field-dependent de Haas–van Alphen oscillations. We previously argued that the large-amplitude oscillations of the magnetic susceptibility could enhance the ohmic dissipation of the magnetic field by continuously generating small-scale, rapidly dissipating field features. This could be important to magnetar field evolution and contribute to their observed higher temperatures. To study this, we performed quasi-3D numerical simulations of electron MHD in a representative volume of neutron star crust matter, for the first time including the magnetization and magnetic susceptibility resulting from Landau quantization. We find that the potential enhancement in the ohmic dissipation rate due to this effect can be a factor ∼3 for temperatures of the order of 10 8 K, and ∼4.5 for temperatures of the order of 5 × 10 7 K, depending on the magnetic field configuration. The nonlinear Hall term is crucial to this amplification: without it, the magnetic field decay is only enhanced by a factor ≲2 even at 5 × 10 7 K. These effects generate a high wavenumber plateau in the magnetic energy spectrum associated with the small-scale de Haas–van Alphen oscillations. Our results suggest that this mechanism could help explain the magnetar heating problem, though due to the effect's temperature-dependence, full magneto-thermal evolution simulations in a realistic stellar model are needed to judge whether it is viable explanation.

Rau, Peter B. (ORCID:0000000152209277)↗
NASA NTRS1968

Analog quantizing circuit.

Analog circuit simulating quantization for analog simulation of hybrid control system, showing quantized output and error signal for wave forcing function

Coon, T. R.↗
NASA NTRS1971

Image coding by adaptive block quantization.

A new source encoder called the adaptive block quantizer is proposed for coding data sources that emit a sequence of correlated real numbers with known first- and second-order statistics. Blocks of source output symbols are first classified and then block quantized in a manner that depends on their classification. The system is optimized relative to both the mean square error and the subjective quality of the reconstructed data for a certain class of pictorial data, and the resulting system performance demonstrated. Some interesting relationships between mean square error and subjective picture quality are presented.

Tasto, M.↗
NASA NTRS1972

Approximate estimation for systems with quantized data.

Estimation of the state of a nonlinear discrete-time system using quantized data is considered. An exact solution for the maximum likelihood estimate is expressed as the solution of a nonlinear two-point boundary-value problem. Approximate recursive solutions for both the maximum likelihood and the conditional-mean estimates are obtained. The results of Monte-Carlo simulations are presented in which the performance of these two algorithms is compared with that of a Kalman filter in which the quantization error is approximated by white noise.-

Clements, K. A.↗
NASA NTRS1972

Instabilities caused by floating-point arithmetic quantization.

It is shown that an otherwise stable digital control system can be made unstable by signal quantization when the controller operates on floating-point arithmetic. Sufficient conditions of instability are determined, and an example of loss of stability is treated when only one quantizer is operated.

Phillips, C. L.↗
NASA NTRS1973

Floating-point system quantization errors in digital control systems

The results are reported of research into the effects on system operation of signal quantization in a digital control system. The investigation considered digital controllers (filters) operating in floating-point arithmetic in either open-loop or closed-loop systems. An error analysis technique is developed, and is implemented by a digital computer program that is based on a digital simulation of the system. As an output the program gives the programing form required for minimum system quantization errors (either maximum of rms errors), and the maximum and rms errors that appear in the system output for a given bit configuration. The program can be integrated into existing digital simulations of a system.

Phillips, C. L.↗
NASA NTRS1973

Note on the error signal of block quantizers.

Demonstration that the error signal incurred by block quantizing stationary data is nonstationary under some conditions. Examples are presented which indicate that the mean square error is largest at the block edges. When block quantizers are used to encode pictures at low bit rates, this effect tends to make the block edges visible in the reconstructed picture.

Tasto, M.↗
NASA NTRS1981

On the correction for quantization effects in signal-to-noise ratio estimation

In sampled data digital telemetry systems the signal to noise ratio (SNR) is typically derived as a function of the moments of the digitized input stream (e.g., the receiver output). This analog to digital conversion process is itself an additional noise source known as the quantization noise. Thus a digitally measured SNR will only approximately represent the SNR of the analog input signal. A procedure (Sheppard's corrections) for correcting moments of any order for this quantization effect is presented.

Howard, L.↗
NASA NTRS1985

Gain-adaptive vector quantization for medium-rate speech coding

A class of adaptive vector quantizers (VQs) that can dynamically adjust the 'gain' of codevectors according to the input signal level is introduced. The encoder uses a gain estimator to determine a suitable normalization of each input vector prior to VQ coding. The normalized vectors have reduced dynamic range and can then be more efficiently coded. At the receiver, the VQ decoder output is multiplied by the estimated gain. Both forward and backward adaptation are considered and several different gain estimators are compared and evaluated. An approach to optimizing the design of gain estimators is introduced. Some of the more obvious techniques for achieving gain adaptation are substantially less effective than the use of optimized gain estimators. A novel design technique that is needed to generate the appropriate gain-normalized codebook for the vector quantizer is introduced. Experimental results show that a significant gain in segmental SNR can be obtained over nonadaptive VQ with a negligible increase in complexity.

Chen, J.-H.↗
NASA NTRS1986

Choosing channel quantization levels and viterbi decoding for space diversity reception over the additive white Guassian noise channel

Previous work in the area of choosing channel quantization levels for a additive white Gaussian noise channel composed of one receiver-demodulator is reviewed, and how this applies to the Deep Space Network composed of several receiver-demodulators (space diversity reception) is shown. Viterbi decoding for the resulting quantized channel is discussed.

Kalson, S.↗
NASA NTRS1986

Table look-up estimation of signal and noise parameters from quantized observables

A table look-up algorithm for estimating underlying signal and noise parameters from quantized observables is examined. A general mathematical model is developed, and a look-up table designed specifically for estimating parameters from four-bit quantized data is described. Estimator performance is evaluated both analytically and by means of numerical simulation, and an example is provided to illustrate the use of the look-up table for estimating signal-to-noise ratios commonly encountered in Voyager-type data.

Vilnrotter, V. A.↗
NASA NTRS1989

Vector quantization

During the past ten years Vector Quantization (VQ) has developed from a theoretical possibility promised by Shannon's source coding theorems into a powerful and competitive technique for speech and image coding and compression at medium to low bit rates. In this survey, the basic ideas behind the design of vector quantizers are sketched and some comments made on the state-of-the-art and current research efforts.

Gray, Robert M.↗
NASA NTRS1989

A VLSI chip set for real time vector quantization of image sequences

The architecture and implementation of a VLSI chip set that vector quantizes (VQ) image sequences in real time is described. The chip set forms a programmable Single-Instruction, Multiple-Data (SIMD) machine which can implement various vector quantization encoding structures. Its VQ codebook may contain unlimited number of codevectors, N, having dimension up to K = 64. Under a weighted least squared error criterion, the engine locates at video rates the best code vector in full-searched or large tree searched VQ codebooks. The ability to manipulate tree structured codebooks, coupled with parallelism and pipelining, permits searches in as short as O (log N) cycles. A full codebook search results in O(N) performance, compared to O(KN) for a Single-Instruction, Single-Data (SISD) machine. With this VLSI chip set, an entire video code can be built on a single board that permits realtime experimentation with very large codebooks.

Baker, Richard L.↗
NASA NTRS1989

Block adaptive quantization of Magellan SAR data

A report is presented on a data compression scheme that will be used to reduce the SAR data rate on the NASA Magellan mission to Venus. The spacecraft has only one scientific instrument, a radar system for imaging the surface, for altimetric profiling of the planet topography, and for measuring radiation from the planet surface. A straightforward implementation of the scientific requirements of the mission results in a data rate higher than can be accommodated by the available system bandwidth. A data-rate-reduction scheme which includes operation of the radar in burst mode and block-adaptive quantization of the SAR data is selected to satisfy the scientific requirements. Descriptions of the quantization scheme and its hardware implementation are given. Burst-mode SAR operation is also briefly discussed.

Kwok, Ronald↗
NASA NTRS1991

The behavior of quantization spectra as a function of signal-to-noise ratio

An expression for the spectrum of quantization error in a discrete-time system whose input is a sinusoid plus white Gaussian noise is derived. This quantization spectrum consists of two components: a white-noise floor and spurious harmonics. The dithering effect of the input Gaussian noise in both components of the spectrum is considered. Quantitative results in a discrete Fourier transform (DFT) example show the behavior of spurious harmonics as a function of the signal-to-noise ratio (SNR). These results have strong implications for digital reception and signal analysis systems. At low SNRs, spurious harmonics decay exponentially on a log-log scale, and the resulting spectrum is white. As the SNR increases, the spurious harmonics figure prominently in the output spectrum. A useful expression is given that roughly bounds the magnitude of a spurious harmonic as a function of the SNR.

Flanagan, M. J.↗