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DOE OSTI2025

Classical Non-Markovian Noise in Symmetry-Preserving Quantum Dynamics

In quantum dynamics, symmetries are vital for identifying and assessing conserved quantities that govern the evolution of a quantum system. When promoted to the open quantum system setting, dynamical symmetries can be negatively altered by system-environment interactions, thus, complicating their analysis. Previous work on noisy symmetric quantum dynamics has focused on the Markovian setting, despite the ubiquity of non-Markovian noise in a number of widely used quantum technologies. Here, in this Letter, we develop a framework for quantifying the impact of non-Markovian noise on symmetric quantum evolution via root space decompositions and the filter function formalism. We demonstrate analytically that symmetry-preserving noise maintains the symmetric subspace, while nonsymmetric noise leads to highly specific leakage errors that are block diagonal in the symmetry representation. We support our findings with numerical studies of a transverse-field Ising model and a quantum error detecting code subject to spatiotemporally correlated multiaxis noise. Our results are broadly applicable, providing new analytic insights into the control and characterization of open quantum system dynamics.

decoherence↗

DOE OSTI2021

Modeling Noise: Paths toward AI-Enabled Stochastic Earth System Models and Parameterizations

Some of the key challenges in Earth system prediction arise from an uncertain representation of unpredictable natural variability, across time and space scales. This variability, hereafter referred to as noise, represents the quantity against which the strength of a signal of interest is measured to assess predictability. Underestimating or overestimating this noise in Earth system models can lead to issues ranging between overconfidence in an erroneous prediction and a lack thereof in an otherwise accurate one. Noise is part of the physical processes in the Earth system and can amplify or damp a signal of interest in a complex manner that is not systematically characterized. Specifically, while there has been significant progress in our understanding of multiscale interactions among known modes of variability (potentially predictable signals), how these are impacted by the noise is not clear. Recent effort toward stochastic parametrization schemes that provide a representation of noise due to uncertain sub-grid processes in climate models (Berner et al., 2017 and references therein) has shown promise not only in reducing biases and improving probabilistic prediction but also in improving the representation of natural variability in the model toward what is observed. However, today’s standard schemes for stochastic parametrization are still simplistic as they do not take the state of the atmosphere into account (other than by the use of multiplicative noise for model tendencies). Furthermore they require hand-tuning and trial-and-error testing for the magnitude of the added noise, which is difficult in a chaotic system that is as complex as the Earth system.

58 GEOSCIENCES↗

NASA NTRS1968

Improved traveling wave maser amplifier

Traveling Wave Maser /TWM/ that operates at S-band frequencies is characterized by a greatly improved gain-bandwidth product with relatively low equivalent-noise temperature. Tests indicate that its performance exceeds that of any other type of S-band amplifier.

Clauss, R. C.↗

NASA NTRS1975

Radiometric performance of the Viking Mars lander cameras

The Viking lander cameras feature an array of 12 silicon photodiodes for electronic focus selection and multispectral imaging. Comparisons of absolute radiometric calibrations of the four cameras selected for the mission to Mars with performance predictions based on their design data revealed minor discrepancies. These discrepancies were caused primarily by the method used to calibrate the photosensor array and apparently also from light reflections internal to the array. The sensitivity and dynamic range of all camera channels are found to be sufficient for high quality pictures, providing that the commandable gains and offsets can be optimized for the scene radiance; otherwise, the quantization noise may be too high or the dynamic range too low for an adequate characterization of the scene.

Huck, F. O.↗

NASA NTRS1976

Computer-aided analysis of CCD linear image sensors

Special test equipment and techniques to collect and process image information from charge coupled devices (CCDs) by digital computer were reviewed. The video channel was traced from the CCD to the direct memory access bus of the Interdata Computer. Software was developed to evaluate and characterize a CCD for (1) dark signal versus temperature relationship, (2) calculation of temporal noise magnitude and noise shape for each pixel, (3) spatial noise into the video chain due to dark signal, (4) response versus illumination relationship (gamma), (5) response versus wavelength of illumination (spectral), (6) optimization of forcing functions, and (7) evaluation of an image viewed by a CCD. The basic software differences and specific examples of each program operating on real data are presented.

Prince, S. S.↗

NASA NTRS1978

Hadamard techniques in optics and their relationship to other multiplexing schemes

Some general properties of multiplexing optical systems for astronomical applications are described. The advantages and disadvantages which characterize Fourier and digitally encoded instruments when faced with any of ten sources of noise are discussed.

Harwit, M.↗

NASA NTRS1991

An improved offset generator developed for Allan deviation measurement of ultra stable frequency standards

Measuring the performance of ultra stable frequency standards such as the Superconducting Cavity Maser Oscillator (SCMO) necessitates improvement of some test instrumentation. The frequency stability test equipment used at JPL includes a 1 Hz Offset Generator to generate a beat frequency between a pair of 100 MHz signals that are being compared. The noise floor of the measurement system using the current Offset Generator is adequate to characterize stability of hydrogen masers, but it is not adequate for the SCMO. A new Offset Generator with improved stability was designed and tested at JPL. With this Offset Generator and a new Zero Crossing Detector, recently developed at JPL, the measurement flow was reduced by a factor of 5.5 at 1 second tau, 3.0 at 1000 seconds, and 9.4 at 10,000 seconds, compared against the previous design. In addition to the new circuit designs of the Offset Generator and Zero Crossing Detector, tighter control of the measurement equipment environment was required to achieve this improvement. The design of this new Offset Generator are described, along with details of the environment control methods used.

R. L. Hamell↗

NASA NTRS2005

Coping with Trial-to-Trial Variability of Event Related Signals: A Bayesian Inference Approach

In electro-neurophysiology, single-trial brain responses to a sensory stimulus or a motor act are commonly assumed to result from the linear superposition of a stereotypic event-related signal (e.g. the event-related potential or ERP) that is invariant across trials and some ongoing brain activity often referred to as noise. To extract the signal, one performs an ensemble average of the brain responses over many identical trials to attenuate the noise. To date, h s simple signal-plus-noise (SPN) model has been the dominant approach in cognitive neuroscience. Mounting empirical evidence has shown that the assumptions underlying this model may be overly simplistic. More realistic models have been proposed that account for the trial-to-trial variability of the event-related signal as well as the possibility of multiple differentially varying components within a given ERP waveform. The variable-signal-plus-noise (VSPN) model, which has been demonstrated to provide the foundation for separation and characterization of multiple differentially varying components, has the potential to provide a rich source of information for questions related to neural functions that complement the SPN model. Thus, being able to estimate the amplitude and latency of each ERP component on a trial-by-trial basis provides a critical link between the perceived benefits of the VSPN model and its many concrete applications. In this paper we describe a Bayesian approach to deal with this issue and the resulting strategy is referred to as the differentially Variable Component Analysis (dVCA). We compare the performance of dVCA on simulated data with Independent Component Analysis (ICA) and analyze neurobiological recordings from monkeys performing cognitive tasks.

Ding, Mingzhou↗

NASA NTRS2006

High-Level Performance Modeling of SAR Systems

SAUSAGE (Still Another Utility for SAR Analysis that s General and Extensible) is a computer program for modeling (see figure) the performance of synthetic- aperture radar (SAR) or interferometric synthetic-aperture radar (InSAR or IFSAR) systems. The user is assumed to be familiar with the basic principles of SAR imaging and interferometry. Given design parameters (e.g., altitude, power, and bandwidth) that characterize a radar system, the software predicts various performance metrics (e.g., signal-to-noise ratio and resolution). SAUSAGE is intended to be a general software tool for quick, high-level evaluation of radar designs; it is not meant to capture all the subtleties, nuances, and particulars of specific systems. SAUSAGE was written to facilitate the exploration of engineering tradeoffs within the multidimensional space of design parameters. Typically, this space is examined through an iterative process of adjusting the values of the design parameters and examining the effects of the adjustments on the overall performance of the system at each iteration. The software is designed to be modular and extensible to enable consideration of a variety of operating modes and antenna beam patterns, including, for example, strip-map and spotlight SAR acquisitions, polarimetry, burst modes, and squinted geometries.

Chen, Curtis↗

NASA NTRS2012

Aircraft Dynamic Modeling in Turbulence

A method for accurately identifying aircraft dynamic models in turbulence was developed and demonstrated. The method uses orthogonal optimized multisine excitation inputs and an analytic method for enhancing signal-to-noise ratio for dynamic modeling in turbulence. A turbulence metric was developed to accurately characterize the turbulence level using flight measurements. The modeling technique was demonstrated in simulation, then applied to a subscale twin-engine jet transport aircraft in flight. Comparisons of modeling results obtained in turbulent air to results obtained in smooth air were used to demonstrate the effectiveness of the approach.

Morelli, Eugene A.↗

NASA NTRS2019

Analysis of Mercury Laser Altimeter Crossovers with Improved Mercury and MESSENGER Ephemerides

Based on previous applications of laser altimetry to planetary geodesy at GSFC [Mazarico et al. (2014),(2016)] and taking advantage of new accurate Mercury and MESSENGER orbits by [Genova et al. (2019)], we analyze altimetric crossovers from the MESSENGER (Mercury Surface, Space Environment, Geochemistry and Ranging) Laser Altimeter (MLA) to solve for orbital and geodetic parameters (e.g., rotation and orientation). We present our results based on a new Python software package recently developed at GSFC that can simulate and process altimetry data in a closed-loop. Realistic simulations of MLA data, including an appropriate range noise from the instrument and realistic terrain roughness, are performed in order to fully characterize the robustness of the solution. The simulation results are then applied to our analysis of the full dataset acquired by the MLA instrument.

Bertone, Stefano↗

NASA NTRS2019

Orbital Debris Radar Measurements from the Haystack Ultra-Wideband Satellite Imaging Radar (HUSIR): 2014-2017

For many years, the NASA Orbital Debris Program Office (ODPO) has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data on the orbital debris environment using the Haystack radar. These measurements are used to characterize the small debris environment in low Earth orbit (LEO), down to a noise-limited size of approximately 5 mm—depending on altitude. The Haystack radar operated by MIT Lincoln Lab underwent upgrades starting in May 2010, with operations resuming in 2014 as the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR). Hence, the data collected beginning in 2014 represents the first dataset available from this upgraded sensor. HUSIR is the primary source of data used by the ODPO to statistically sample orbital debris in the 5-mm to 10-cm size regime in LEO and is a key source of data to build and validate the NASA Orbital Debris Engineering Model. In this paper, we will present recent results from measurements performed during the US Government fiscal years 2014 – 2017. Using the NASA Size Estimation Model, a method based on laboratory radar measurements of debris, we will compare the size distributions of selected orbital debris populations over this 4-year period and flux measurements of orbital debris greater than 1 cm.

Murray, James↗

NASA NTRS2024

NASA Orbital Debris Radar Measurements by the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR)

For many years, the NASA Orbital Debris Program Office (ODPO) has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data on the orbital debris environment using the Haystack radar. These measurements are used to characterize the small debris environment in low Earth orbit (LEO), down to a noise-limited size of approximately 5 mm—depending on altitude. The Haystack radar operated by MIT/LL underwent upgrades starting in May 2010, with operations resuming in 2014 as the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR). HUSIR is the primary source of data used by the ODPO to statistically sample orbital debris in the 5-mm to 10-cm size regime in LEO and is a key source of data to build and validate the NASA Orbital Debris Engineering Model. In this presentation, we will present recent HUSIR results and show how NASA uses them to understand the orbital debris environment.

Mark Matney↗

NASA NTRSDate not supplied

Pre-Launch Characterization of the Hyperspectral Ocean Color Instrument on NASA’s Pace Mission

Launched in February 2024, the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. Like its predecessors, OCI provides two day global coverage of top-of-atmosphere radiances. Unlike its predecessors, OCI covers a spectral range from 340 nm to 2260 nm. Below 900 nm, OCI provides hyperspectral radiances sampled every 2.5 nm or 1.25nm, with a bandwidth of 5 nm for each channel. Its spatial resolution is about 1.2km. The high radiometric accuracy of OCI was made possible by a thorough and extensive prelaunch characterization campaign, conducted at NASA’s Goddard Space Flight Center. This presentation describes the prelaunch radiometric characterization (approach and results) of OCI, such as e.g. the linearity correction, signal to noise ratio, polarization, IFOV, relative spectral response, radiometric gain, temperature sensitivity, optical crosstalk, and response versus scan angle.

Gerhard Meister↗

NASA NTRSDate not supplied

On-Orbit OCI Characterization Measurements from the first 6 Months of the PACE Mission

The Ocean Color Instrument (OCI) on NASA’s Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission has been providing data to the science community since April 2024. OCI is a hyperspectral imager, providing almost daily global coverage, at a spatial resolution of 1.2km. Its design specifications were optimized for ocean color and atmospheric applications, but terrestrial studies could benefit from its hyperspectral coverage as well. The ocean color requirements called for very high radiometric accuracy, which could benefit a wide variety of applications. This paper presents results from the first 6 months of on-orbit calibration and characterization measurements, including absolute calibration, spectral registration, temporal trending of radiometric sensitivity, signal to noise ratio, and linearity, with a focus on the commissioning results obtained in the first 2 months after launch.

calibration↗

NASA NTRSDate not supplied

On-Orbit OCI Characterization Measurements from the first 6 Months of the PACE Mission

calibration↗

DOE OSTI2023

DarkNESS: Characterization of Space Multi-Chip Module Skipper-CCDs

The DarkNESS mission is to send a 6U CubeSat fitted with an array of skipper-CCDs to see how well these sensors operate in Low Earth Orbit: take measurements of x-rays from the galactic center and strongly interacting sub-GeV dark matter from Cygnus X-1. Skipper-CCDs allow for low-noise astronomical observations which can extend the discovery reach for direct dark matter search experiments. This paper will discuss the characterization of the space Multi-Chip Module (sMCM) equipped with skipper-CCDs, and the challenges it faces during testing in the lab environment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Essential barrier height and a probabilistic approach in characterizing potential landscape

In this work we propose a probabilistic approach to investigate the shape of landscapes of multi-dimensional potential functions. Under a suitable coupling scheme, two copies of the overdamped Langevin dynamics associated with the potential function are coupled, and the coupling times are collected. Assuming a set of intuitive yet technically challenging conditions on the coupling scheme, it is shown that the tail distributions of the coupling times exhibit qualitatively different dependencies on the noise magnitude for single-well versus multi-well potential functions. More specifically, for convex single-well potentials, the negative tail exponent of the coupling time distribution is uniformly bounded away from zero by the convexity parameter and is independent of the noise magnitude. In contrast, for multi-well potentials, the negative tail exponent decreases exponentially as the noise vanishes, with the decay rate governed by the essential barrier height, a quantity introduced in this paper to characterize the non-convex nature of the potential function. Numerical investigations are conducted for a variety of examples, including the Rosenbrock function, interacting particle systems, and loss functions arising in artificial neural networks. These examples not only illustrate the theoretical results in various contexts but also provide crucial numerical validation of the conjectured assumptions, which are essential to the theoretical analysis yet lie beyond the reach of standard technical tools.

97 MATHEMATICS AND COMPUTING↗