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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Magneto-Optical Sensing Beyond the Shot Noise Limit

Magneto-optical sensors including spin noise spectroscopies and magneto-optical Kerr effect microscopies are now ubiquitous tools for materials characterization that can provide new understanding of spin dynamics, hyperfine interactions, spin-orbit interactions, and charge-carrier g-factors. Both interferometric and intensity-difference measurements can provide photon-shot-noise-limited sensitivity, but further improvements in sensitivity with classical resources require either increased laser power that can induce unwanted heating and electronic perturbations or increased measurement times that can obscure out-of-equilibrium dynamics and slow experimental throughput. Proof-of-principle measurements have already demonstrated quantum enhanced spin noise measurements with a squeezed readout field that are likely to be critical to the nonperturbative characterization of spin excitations in quantum materials that emerge at low temperatures. Here, a truncated nonlinear interferometric readout for low-temperature magneto-optical Kerr effect and related magneto-optical microscopies that is accessible with today's quantum optical resources is proposed. 10 nrad/$\sqrt{Hz}$ sensitivity is achievable with optical power as small as 1 µW. As a result, measurements may be performed at temperatures as low as 83 mK in commercially available dilution refrigerators. This combination of high sensitivity and low operating temperature is impossible to achieve with any classical measurement. The quantum advantage for the proposed measurements persists even in the limit of large loss and small squeezing parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Multiplicative noise and the diffusion of conserved densities

Stochastic fluid dynamics governs the long time tails of hydrodynamic correlation functions, and the critical slowing down of relaxation phenomena in the vicinity of a critical point in the phase diagram. In this work we study the role of multiplicative noise in stochastic fluid dynamics. Multiplicative noise arises from the dependence of transport coefficients, such as the diffusion constants for charge and momentum, on fluctuating hydrodynamic variables. We study long time tails and relaxation in the diffusion of a conserved density (model B), and a conserved density coupled to the transverse momentum density (model H). Careful attention is paid to fluctuation-dissipation relations. We observe that multiplicative noise contributes at the same order as non-linear interactions in model B, but is a higher order correction to the relaxation of a scalar density and the tail of the stress tensor correlation function in model H.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Low Noise Frequency-Domain Multiplexing of TES Bolometers Using SQUIDs at Sub-Kelvin Temperature

Digital Frequency-Domain Multiplexing (DfMux) is a technique that uses MHz superconducting resonators and Superconducting Quantum Interference Device (SQUID) arrays to read out sets of transition edge sensors. DfMux has been used by several Cosmic Microwave Background experiments, including most recently POLARBEAR-2 and SPT-3 G with multiplexing factors as high as 68, and is the baseline readout technology for the planned satellite mission LiteBIRD. Here, we present recent work focused on improving DfMux readout noise, reducing parasitic impedance, and improving sensor operation. We have achieved a substantial reduction in stray impedance by integrating the sensors, resonators, and SQUID array onto a single-carrier board operated at 250 mK. This also drastically simplifies the packaging of the cryogenic components and leads to better-controlled crosstalk. We demonstrate a low readout noise level of 8.6 pA/Hz1 1/2 , which was made possible by operating the SQUID array at a reduced temperature and with a low dynamic impedance. This is a factor of two improvement compared to the achieved readout noise level in currently operating Cosmic Microwave Background experiments using DfMux and represents a critical step toward maturation of the technology for the next generation of instruments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The Timepix4 analog front-end design: Lessons learnt on fundamental limits to noise and time resolution in highly segmented hybrid pixel detectors

This manuscript describes the optimization of the front-end readout electronics for high granularity hybrid pixel detectors. The theoretical study aims at minimizing the noise and jitter. The model presented here is validated with both circuit post layout simulations and measurements on the Timepix4 Application Specific Integrated Circuit (ASIC). The analog front-end circuit and the procedure to optimize the dimensions of the main transistors are described with detail. The Timepix4 is the most recent ASIC designed in the framework of the Medipix4 Collaboration. It was manufactured in 65nm CMOS process, and consists of a four side buttable matrix of 448 × 512 pixels with 55µm pitch. The analog front-end has a gain of ~36mV/ke - when configured in High Gain Mode, and ~20mV/ke - when configured in Low Gain Mode. The Equivalent Noise Charge (ENC) is ~68e - rms and ~80e - rms in High Gain Mode and in Low Gain Mode respectively. In event driven mode the incoming hits can be time stamped within a ~ 200ps time bin and the chip can deal with a maximum flux of ~ 3.6MHzmm –2 s –1 . In photon counting mode, the chip can deal with up to ~ 5GHzmm –2 s –1 . The routine designed to optimize the Timepix4 front-end is then used to analyze the performance limits in terms of jitter and noise for Charge Sensitive Amplifiers in pixel detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Noise signal identification in time projection chamber data using deep learning model

Deep learning has been employed in various scientific fields and has provided promising results. Here, in this study, a deep learning classifier was implemented to improve the quality of data obtained from a time projection chamber. Digital waveforms of the detected signals were classified into the following three categories: particles, noises, and particles piled up with noises. A simple 1-dimensional convolutional neural network was developed for the classification. The model demonstrated an excellent performance on the test dataset. Its practical performance was also examined using track images and particle identification plots by comparing the original and clean data without the noise signals. The comparison clearly showed that the deep learning model improved the quality of data. The current study presents an effective application of the deep learning model for the time projection chamber data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Impact of dynamics, entanglement and Markovian noise on the fidelity of few-qubit digital quantum simulation

Quantum algorithms have been proposed to accelerate the simulation of the chaotic dynamical systems that are ubiquitous in the physics of plasmas. Quantum computers without error correction might even use noise to their advantage to calculate the Lyapunov exponent by measuring the Loschmidt echo fidelity decay rate. For the first time, digital Hamiltonian simulations of the quantum sawtooth map, performed on the IBM-Q quantum hardware platform, show that the fidelity decay rate of a digital quantum simulation increases during the transition from dynamical localization to chaotic diffusion in the map. The observed error per CNOT gate increases by $1.5{\times }$ as the dynamics varies from localized to diffusive, while only changing the phases of virtual RZ gates and keeping the overall gate count constant. A gate-based Lindblad noise model that captures the effective change in relaxation and dephasing errors during gate operation qualitatively explains the effect of dynamics on fidelity as being due to the localization and entanglement of the states created. Specifically, highly delocalized states that are entangled with random phases show an increased sensitivity to dephasing and, on average, a similar sensitivity to relaxation as localized states. In contrast, delocalized unentangled states show an increased sensitivity to dephasing but a lower sensitivity to relaxation. This gate-based Lindblad model is shown to be a useful benchmarking tool by estimating the effective Lindblad coherence times during CNOT gates and finding a consistent $2\unicode{x2013}3{\times }$ shorter $T_2$ time than reported for idle qubits. Thus, the interplay of the dynamics of a simulation with the noise processes that are active can strongly influence the overall fidelity decay rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Identifying Different Classes of Seismic Noise Signals Using Unsupervised Learning

Abstract Proper classification of nontectonic seismic signals is critical for detecting microearthquakes and developing an improved understanding of ongoing weak ground motions. We use unsupervised machine learning to label five classes of nonstationary seismic noise common in continuous waveforms. Temporal and spectral features describing the data are clustered to identify separable types of emergent and impulsive waveforms. The trained clustering model is used to classify every 1 s of continuous seismic records from a dense seismic array with 10–30 m station spacing. We show that dominate noise signals can be highly localized and vary on length scales of hundreds of meters. The methodology demonstrates the complexity of weak ground motions and improves the standard of analyzing seismic waveforms with a low signal‐to‐noise ratio. Application of this technique will improve the ability to detect genuine microseismic events in noisy environments where seismic sensors record earthquake‐like signals originating from nontectonic sources.

Johnson, Christopher W.↗
DOE OSTI2021

Boosting the signal-to-noise of low-field MRI with deep learning image reconstruction

Recent years have seen a resurgence of interest in inexpensive low magnetic field (< 0.3 T) MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these advances have focused on improving hardware and signal acquisition strategies, and far less on the use of advanced image reconstruction methods to improve attainable image quality at low field. We describe here the use of our end-to-end deep neural network approach (AUTOMAP) to improve the image quality of highly noise-corrupted low-field MRI data. We compare the performance of this approach to two additional state-of-the-art denoising pipelines. We find that AUTOMAP improves image reconstruction of data acquired on two very different low-field MRI systems: human brain data acquired at 6.5 mT, and plant root data acquired at 47 mT, demonstrating SNR gains above Fourier reconstruction by factors of 1.5- to 4.5-fold, and 3-fold, respectively. In these applications, AUTOMAP outperformed two different contemporary image-based denoising algorithms, and suppressed noise-like spike artifacts in the reconstructed images. The impact of domain-specific training corpora on the reconstruction performance is discussed. The AUTOMAP approach to image reconstruction will enable significant image quality improvements at low-field, especially in highly noise-corrupted environments.

42 ENGINEERING↗
DOE OSTI2021

Stochastic density functional theory: Real- and energy-space fragmentation for noise reduction

Stochastic density functional theory (sDFT) is becoming a valuable tool for studying ground-state properties of extended materials. The computational complexity of describing the Kohn-Sham orbitals is replaced by introducing a set of random (stochastic) orbitals leading to linear and often sub-linear scaling of certain ground-state observables at the account of introducing a statistical error. Schemes to reduce the noise are essential, for example, for determining the structure using the forces obtained from sDFT. Recently, we have introduced two embedding schemes to mitigate the statistical fluctuations in the electron density and resultant forces on the nuclei. Both techniques were based on fragmenting the system either in real space or slicing the occupied space into energy windows, allowing for a significant reduction in the statistical fluctuations. For chemical accuracy, further reduction of the noise is required, which could be achieved by increasing the number of stochastic orbitals. However, the convergence is relatively slow as the statistical error scales as 1 / N &#x3C7; according to the central limit theorem, where N χ is the number of random orbitals. In this paper, we combined the embedding schemes mentioned above and introduced a new approach that builds on overlapped fragments and energy windows. The new approach significantly lowers the noise for ground-state properties, such as the electron density, total energy, and forces on the nuclei, as demonstrated for a G-center in bulk silicon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Robust identification of multiple-input single-output system response for efficient pickup noise removal from tokamak diagnostics

We report electromagnetic pickup noise in the tokamak environment imposes an imminent challenge for measuring weak diagnostic photocurrents in the nA range. The diagnostic signal can be contaminated by an unknown mixture of crosstalk signals from coils powered by currents in the kA range. To address this issue, an algorithm for robust identification of linear multi-input single-output (MISO) systems has been developed. The MISO model describes the dynamic relationship between measured signals from power sources and observed signals in the diagnostic and allows for a precise subtraction of the noise component. The proposed method was tested on experimental diagnostic data from the DIII-D tokamak, and it has reduced noise by up to 20 dB in the 1–20 kHz range.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Noise reduction of stochastic density functional theory for metals

Density Functional Theory (DFT) has become a cornerstone in the modeling of metals. However, accurately simulating metals, particularly under extreme conditions, presents two significant challenges. First, simulating complex metallic systems at low electron temperatures is difficult due to their highly delocalized density matrix. Second, modeling metallic warm-dense materials at very high electron temperatures is challenging because it requires the computation of a large number of partially occupied orbitals. This study demonstrates that both challenges can be effectively addressed using the latest advances in linear-scaling stochastic DFT methodologies. Despite the inherent introduction of noise into all computed properties by stochastic DFT, this research evaluates the efficacy of various noise reduction techniques under different thermal conditions. Our observations indicate that the effectiveness of noise reduction strategies varies significantly with the electron temperature. Furthermore, we provide evidence that the computational cost of stochastic DFT methods scales linearly with system size for metal systems, regardless of the electron temperature regime.

Chemistry↗
DOE OSTI2025

Low two-level-system noise in hydrogenated amorphous silicon

At sub-Kelvin temperatures, two-level systems (TLSs) present in amorphous dielectrics source a permittivity noise, degrading the performance of a wide range of devices using superconductive resonators such as qubits or kinetic inductance detectors. We report here on measurements of TLS noise in hydrogenated amorphous silicon (a-Si:H) films deposited by plasma-enhanced chemical vapor deposition in superconductive lumped element resonators using parallel-plate capacitors. In conclusion, the TLS noise results presented in this article for two recipes of a-Si:H improve on the best results achieved in the literature by a factor >5 for a-Si:H and other amorphous dielectrics and are comparable to those observed for resonators deposited on crystalline dielectrics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Comparative Evaluation of Spectral Methods for Robust Reactor Noise Estimation

Reactor noise analysis provides a noninvasive means to determine neutron kinetic parameters from stochastic fluctuations in detector signals. However, standard cross-power spectral density (CPSD) analyses can be sensitive to numerical processing choices, which may introduce processing-dependent systematic shifts in estimates of the prompt neutron decay constant (α) and limit reproducibility. This study uses a hybrid multitaper–Welch spectral estimator to analyze subcritical noise measurements from a fast-spectrum critical assembly. The decay constant α was extracted using three frequency-domain methods: the CPSD, the magnitude-squared coherence (MSC), and the generalized magnitude-squared coherence (GMSC). These coherence-based estimators normalize detector auto-spectral structure and are expected to reduce the sensitivity of fitted α values to processing parameters. A Sobol global sensitivity analysis identified which numerical inputs most strongly influence the fitted values of α. All estimators produced a linear dependence of α on inverse count rate, with delayed-critical extrapolations near 1.7 × 10 4 s −1 , in agreement within 8% of MCNP6.3 KOPTS benchmark calculations. Sensitivity results show that while the CPSD depends on both time-bin width and taper selection, the MSC and GMSC are dominated by time-bin width alone, indicating reduced parameter coupling and greater robustness to processing variability. These findings demonstrate the feasibility and practical value of coherence-based spectral estimators for extracting α from reactor noise and support their broader application to multi-detector and irregular datasets in subcritical system characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Characterization of the Cherenkov Photon Background for Low-noise Silicon Detectors in Space

Future space observatories that seek to perform imaging and spectroscopy of faint astronomical sources will require ultra-low-noise detectors that are sensitive over a broad wavelength range. Silicon charge-coupled devices (CCDs), such as EMCCDs, skipper CCDs, multi-amplifier sensing CCDs, and single-electron sensitive read out CCDs have demonstrated the ability to detect and measure single photons from X-ray energies to near the silicon band gap (∼1.1 μm), making them candidate technologies for this application. Here, in this context, we study a relatively unexplored source of low-energy background coming from Cherenkov radiation produced by energetic cosmic rays traversing a silicon detector. We present a model for Cherenkov photon production and absorption that is calibrated to laboratory data, and we use this model to characterize the residual background rate for ultra-low-noise silicon detectors in space. We study how the Cherenkov background rate depends on detector thickness, variations in solar activity, and the contribution of heavy cosmic ray species (Z > 2). We find that for thick silicon detectors, such as those required to achieve high quantum efficiency at long wavelengths, the rate of cosmic-ray-induced Cherenkov photon production is comparable to other detector and astrophysical backgrounds. We apply our Cherenkov background model to simulated spectroscopic observations of extra-solar planets, and we find that thick detectors continue to outperform their thinner counterparts at longer wavelengths despite a larger Cherenkov background rate. Furthermore, we find that minimal masking of cosmic-ray tracks continues to maximize the signal-to-noise ratio of very faint sources despite the existence of extended halos of Cherenkov photons.

Astronomical detectors↗
DOE OSTI2024

Simulation of shot noise effects in the EIC strong hadron cooling accelerator using real number of electrons

In the electron ion collider design, in order to achieve the peak luminosity 10 34 /cm 2 /s with a reasonable lifetime, an efficient coherent electron cooling scheme was proposed to reduce the hadron beam emittance growth. Such a cooling scheme requires a good electron beam quality with a small energy spread. However, the shot noise in the electron beam through the accelerator might be amplified due to the microbunching instability and degrades the electron beam quality in the modulator section of the strong hadron cooling channel and correspondingly cooling rate. In this study, we report on self-consistent simulations of these effects using a real number of electrons to capture the details of shot noise and analysis of the shot noise growth through the accelerator.

Qiang, Ji↗
DOE OSTI2021

Characterisation of signal-induced noise in Hamamatsu R11265 Multianode Photomultiplier Tubes

Signal-induced noise is observed in Hamamatsu R11265 Multianode Photomultiplier Tubes, manifesting up to several microseconds after the single photoelectron response signal and localised in specific anodes. The mean number of noise pulses varies between devices, and shows significant dependence on the applied high-voltage. The characterisation of this noise and the mitigation strategies to perform optimal single-photon counting at 40 MHz, as required by the LHCb Ring-Imaging Cherenkov detectors, are reported.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

MAGIS-100 environmental characterization and noise analysis

We investigate and analyze site specific systematics for the MAGIS-100 atomic interferometry experiment at Fermi National Accelerator Laboratory. As atom interferometers move out of the laboratory environment passive and active mitigation for noise sources must be implemented. To inform the research and development of the experiment design, we measure ambient temperature, humidity, and vibrations of the installation site. We find that temperature fluctuations will necessitate enclosures for critical subsystems and a temperature controlled laser room for the laser system. We also measure and analyze the vibration spectrum above and below ground for the installation site. The seismic vibration effect of gravity gradient noise is also modeled using input from a low-noise seismometer at multiple locations and a mitigation scheme is studied using a stochastic simulation and characterized by a suppression factor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

How the discovery of Cold Noise delayed the production of ATLAS ITk strip tracker modules by a year

Here, the construction of the ATLAS strip tracker barrel will require the assembly of 12,000 barrel detector modules over the course of 3.5 years. In 2022, during the module pre-production phase, modules were found to display clusters of noisy channels outside required specifications when tested at operating temperatures (-35°C), called “Cold Noise”. Extensive investigations into the cause and mechanism of Cold Noise interrupted pre-production and occupied most barrel module assembly sites. This contribution presents an overview of the year-long investigations into Cold Noise, the final identification of the underlying mechanism and necessary changes for the transition to production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗