Search NASA⌕ Search

SEARCH · Search NASA

Results for “SIGNAL PROCESSING”

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 541 records · Page 30

Enhancing Automotive Intrusion Detection Through Multi-Modal Fusion: A CAN FD-LiDAR Approach

As vehicles become smarter and more autonomous, they increasingly depend on advanced sensors and communication technologies to operate securely. However, such growing dependence on technology—whether it’s CAN (Controller Area Network) for internal communication or LiDAR (Light Detection and Ranging) for sensing the world around them—also expands the attack surface for the types of cyber attacks. Traditional intrusion detection systems (IDS) typically monitor these systems in isolation, limiting their ability to detect sophisticated, crosssystem attacks. To address this, we propose a multi-modal fusion approach that combines real-world CAN FD signals (from the HCRL dataset) with LiDAR features (from the nuScenes dataset) to enhance attack detection. Our method employs a twostage ensemble approach. Calibrated XGBoost and LightGBM models initially process CAN FD (Fuzzing Data) and LiDAR data independently, detecting timing anomalies and space abnormalities. They are subsequently logarithmically combined with a logistic regression meta-model along with 17 engineered features capturing cross-modal behavior, prediction conflicts, and nonlinear interactions. This approach achieves an AUC of 0.87 and an F1-score of 0.82, surpassing single-modality baselines and early fusion methods, at merely 2 ms inference latency. Compared with deep learning competitors, it is 3 times more efficient, providing a lightweight, interpretable, and real time solution to automotive cybersecurity.

97 MATHEMATICS AND COMPUTING↗

WaveDenoiser

We developed a robust deep learning model to effectively reduce background noise in the time domain from seismic waveforms. The deep learning model processes a 57-second three-component seismogram to predict and generate a denoised seismogram. The training was conducted using the benchmark STEAD dataset, which comprises globally distributed earthquake signals recorded at local distances ranging from 0 to 350 kilometers.

Chai, Chengping [Oak Ridge National Laboratory (OR↗

Final Technical Report: Testing the robustness of CMB-S4 inflation measurements to foreground models

This report summarizes the research activities for DOE award SC0024462, which focused on enhancing the robustness of CMB-S4 inflation measurements by characterizing and mitigating Galactic foreground interference. The project grounded foreground models in the physical processes of the Interstellar Medium with MHD and semi-analytic filament models, and developed analysis pipelines, such as Needlet Internal Linear Combination (NILC) techniques, to isolate faint cosmological signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Background cancellation for frequency-selective quantum sensing

A key challenge in quantum sensing is the detection of weak time dependent signals, particularly those that arise as specific frequency perturbations over a background field. Conventional methods usually demand complex dynamical control of the quantum sensor and heavy classical post-processing. We propose a quantum sensor that leverages time independent interactions and entanglement to function as a passive, tunable, thresholded frequency filter. By encoding the frequency selectivity and thresholding behavior directly into the dynamics, the sensor is responsive only to a target frequency of choice whose amplitude is above a threshold. This approach circumvents the need for complex control schemes and reduces the post-processing overhead.

Puig, Ricard [Los Alamos; Ecole Polytechnique, Lau↗

A novel regulator of the fungal phosphate starvation response revealed by transcriptional profiling and DNA affinity purification sequencing

Cells must accurately sense and respond to nutrients to compete for resources and establish growth. Phosphate is a critical nutrient source necessary for signaling, energy metabolism, and synthesis of nucleic acids, phospholipids, and cellular metabolites. During phosphate limitation, fungi import phosphate from the environment and liberate phosphate from phosphate-containing molecules in the cell. In the model filamentous fungus Neurospora crassa, the phosphate starvation response is regulated by the conserved transcription factor NUC-1. The activity of NUC-1 is repressed by a complex of the cyclin-dependent kinase MDK-1 and the cyclin PREG when phosphate is plentiful. When phosphate is limiting, NUC-1 repression by MDK-1/PREG is relieved by the cyclin-dependent kinase inhibitor NUC-2. We investigated the global response of N. crassa to phosphate starvation. During phosphate starvation, NUC-1 directly activated the expression of genes encoding phosphatases, nucleases, and a phosphate transporter and directly repressed genes associated with the ribosome. Additionally, NUC-1 indirectly activated the expression of an uncharacterized transcription factor, which we named nuc-3. NUC-3 directly repressed the expression of genes involved in phosphate acquisition and liberation after an extended period of phosphate starvation. Additionally, NUC-3 directly repressed the expression of the cyclin-dependent kinase inhibitor nuc-2. Thus, through the combination of NUC-3 direct repression of genes in the phosphate starvation response and nuc-2, an activator of the phosphate starvation response, NUC-3 serves to act as a brake on the phosphate starvation response after an extended period of phosphate starvation. This braking mechanism could reduce transcription, a phosphate-intensive process, under conditions of extended phosphate limitation.IMPORTANCEFungi have evolved regulatory networks to respond to available nutrients. Phosphate is often a limiting nutrient for fungi that is critical for many cellular functions, including nucleic acid and phospholipid biosynthesis, cell signaling, and energy metabolism. The fungal response to phosphate limitation is important in interactions with plants and animals. We investigated the global transcriptional response to phosphate starvation and the role of a major transcriptional regulator, NUC-1, in the model filamentous fungus Neurospora crassa. Our data show that NUC-1 is a bifunctional transcription factor that directly activates phosphate acquisition genes, while directly repressing genes associated with phosphate-intensive processes. NUC-1 indirectly regulates an uncharacterized transcription factor, which we named nuc-3. NUC-3 directly represses phosphate acquisition genes and nuc-2, an activator of the phosphate starvation response, during extended periods of phosphate starvation. Thus, NUC-3 acts as a brake on the phosphate starvation response to reduce phosphate-intensive activities, like transcriptional activation, when phosphate starvation persists.

DNA affinity purification sequencing↗

Commissioning of the Mu2e tracker DAQ, planning for the Vertical Slice Test and pre-pattern recognition studies

The primary objective of the Mu2e experiment at Fermilab is to search for the neutrino-less coherent $\mu \rightarrow e$ conversion in the field of an aluminum nucleus ($\mu^- \text{Al} \rightarrow e^- \text{Al}$). The signature of this process is a monochromatic Conversion Electron (CE) with an energy of approximately 104.97 MeV \cite{bartoszek2015mu2e}. Within the Standard Model (SM), the branching ratio for this process, including neutrino masses and oscillation, is expected to be less than $\mathcal{O}(10^{-50})$. This value is far beyond current experimental capabilities. However, models of physics beyond the SM predict much higher relative rates, approaching an observable level. The SINDRUM II experiment set an upper limit on muon conversion at $7 \times 10^{-13}$ (90\% CL) on Au target \cite{SINDRUMII:2006dvw}, and the Mu2e collaboration aims to improve this limit by four orders of magnitude. Observing this process would provide a clear evidence of physics beyond the Standard Model. A brief discussion of the theoretical and experimental aspects is provided in Chapter \ref{intr}. Mu2e adopts a sophisticated experimental setup to achieve its goals, further described in Chapter \ref{mu2echapter}. The central part of the Mu2e detector is the tracker, that consists of 18 tracking stations. The tracker must provide excellent momentum resolution, approximately 1 MeV/c, to distinguish the monochromatic CE signal from the background. To minimize the energy losses, a straw tube tracker will be used \cite{bobbb}. Chapter \ref{chaptertrk} provides an overview of the straw tracker design and its working principles. This Thesis presents a comprehensive study of the Mu2e tracker, covering complementary aspects from initial commissioning to optimization and first steps of the calibration processes. My work at Fermilab has been focused on the complete Data Acquisition (DAQ) testing from both hardware and software perspectives. I was involved in the commissioning of the Mu2e DAQ system and the Vertical Slice Test (VST) of the tracker. The VST encompasses the entire testing chain, from the straws to the readout, and to processed data on disk. I was also focused on the offline analysis, especially on pre-pattern recognition studies, to explore the best methods for identifying $\delta$-electrons during the data taking. Chapter \ref{commissioning} details the commissioning of the tracker DAQ system, emphasizing the importance of understanding of the readout process before the data acquisition. This includes validating the readout logic and firmware through Monte Carlo simulations to confirm functionality and buffering, monitoring the quality of the data from the tracker preamplifiers and front-end electronics, and assessing overall DAQ performance to ensure reliability during future calibration and data-taking. Chapter \ref{planning} discusses the initial steps towards the tracker calibration. The ultimate goal is to perform a time calibration of the first assembled station of the tracker using cosmic muons, aiming for a longitudinal hit position resolution better than 4 cm. This involves determining the signal propagation times and channel-to-channel delays. I performed a Monte Carlo study to determine the impact of the station orientation on the quality of the calibration, in particular on the cosmic track reconstruction, focusing on potential biases that could arise. These studies provide essential insights into the operation, optimization, and calibration of the Mu2e tracker system. Given the high data volume expected during Mu2e operations, estimated at approximately 7 PBytes per year, optimizing memory usage and minimizing CPU consumption are critical. A significant challenge lies in effectively flagging $\delta$-electron hits, which are the primary source of hits in the tracker, without compromising the efficiency of CE hit detection and track reconstruction. A detailed study of pre-pattern recognition and a thorough comparison of two $\delta$-electron flagging algorithms is provided in Chapter \ref{delta}. In Chapter \ref{conclusions}, the findings are concisely summarized, offering a comprehensive synthesis of the research and emphasizing the key insights derived from this study.

43 PARTICLE ACCELERATORS↗

Energy-enhanced dimension eight SMEFT effects in VBF Higgs production

We study Higgs boson production via vector boson fusion at the LHC, focusing on the process pp → H + jj and capturing the leading energy-enhanced contributions within the Standard Model Effective Field Theory (SMEFT) up to order 1/Λ$^{4}$. Employing energy-scaling arguments, we predict the magnitude of each higher-dimensional operator’s contribution. Utilizing the geometric formulation of SMEFT, our analysis incorporates dimension-eight operators not previously considered. We find that the kinematics of vector boson fusion — characterized by two highly forward jets — tend to suppress contributions from higher-dimensional operators, requiring a lower scale Λ for SMEFT effects to become observable. This suggests that the SMEFT remains valid for lower Λ than expected. Combined with the fact that LEP constrains the dimension-six operators with the most considerable impact on vector boson fusion, a regime exists where dimension-eight operators can have significant effects. In many cases, these dimension-eight operators also influence associated production processes like pp → HV(jj), though differences in analysis cuts and kinematics mean this is not always the case. Our findings provide insights that could refine the search for SMEFT signals in collider experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ALICE upgrades during the LHC Long Shutdown 2

A Large Ion Collider Experiment (ALICE) has been conceived and constructed as a heavy-ion experiment at the LHC. During LHC Runs 1 and 2, it has produced a wide range of physics results using all collision systems available at the LHC. In order to best exploit new physics opportunities opening up with the upgraded LHC and new detector technologies, the experiment has undergone a major upgrade during the LHC Long Shutdown 2 (2019–2022). This comprises the move to continuous readout, the complete overhaul of core detectors, as well as a new online event processing farm with a redesigned online-offline software framework. These improvements will allow to record Pb-Pb collisions at rates up to 50 kHz, while ensuring sensitivity for signals without a triggerable signature.

47 OTHER INSTRUMENTATION↗

Nanometer-Scale Acoustic Wave Packets Generated by Stochastic Core-Level Photoionization Events

We demonstrate that the absorption of femtosecond hard x-ray pulses excites quasispherical, high-amplitude, and high-wave-vector coherent acoustic phonon wave packets using an all hard-x-ray pump-probe scattering experiment. The time- and momentum-resolved diffuse scattering signal is consistent with an ensemble of 3D strain wave packets induced by the rapid electron cascade dynamics following photoionization at uncorrelated excitation centers. We quantify key parameters of this process, including the localization size of the stress field and the photon energy conversion efficiency into elastic energy. The parameters are determined by the photoelectron and Auger electron cascade dynamics, as well as the electron-phonon interaction. In particular, we obtain the localization size of the observed strain wave packet to be 1.5 and 2.5 nm for bulk SrTiO 3 and KTaO 3 single crystals, respectively. The results provide crucial information on the mechanism of x-ray energy deposition into matter and shed light on the shortest collective length scales accessible to coherent acoustic phonon generation using x-ray excitation. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗

Development and characterization of the flight model spectrometer onboard LuSEE-Night

The Lunar Surface Electromagnetics Experiment - Night, LuSEE-Night, is a low-frequency radio astronomy experiment that will explore the cosmic Dark Ages signal on the radio-quiet far side of the Moon. Here, the LuSEE-Night carries a radio frequency spectrometer consisting of a set of antennas, analog and digital processing electronics, and will be launched by NASA’s Commercial Lunar Payload Services in 2025. The spectrometer is designed to observe the spectrum of the radio sky in the 0.5-50MHz band. The flight model (FM) of the four-channel spectrometer has been developed. The FM has been characterized for linearity, gain, noise, and their temperature dependence, confirming that the FM meets all the requirements for LuSEE-Night.

47 OTHER INSTRUMENTATION↗

Demonstration and performance of an online data selection algorithm for liquid argon time projection chambers using MicroBooNE

The MicroBooNE detector is a liquid argon time projection chamber (LArTPC) that produces three-dimensional images of particle interactions using ionization charge collected by anode wire plane arrays and scintillation light collected by a light detection system. In addition to testing long-standing experimental neutrino anomalies and performing measurements of neutrino interactions with argon nuclei using the Fermilab Booster Neutrino Beam, MicroBooNE aims to develop methodologies for rare beyond the Standard Model and off-beam physics searches. Looking ahead to the upcoming Deep Underground Neutrino Experiment (DUNE), with MicroBooNE serving as a valuable testbed, achieving high sensitivity and livetime for off-beam physics while satisfying data processing and storage constraints will require data-driven, intelligent, and online or real-time data selection techniques. These techniques are essential for reducing data rates and preserving rare signals with high accuracy. In this paper, we describe a fast data selection algorithm suitable for online execution to identify electrons from stopping cosmic ray muons in the MicroBooNE detector utilizing ionization charge information, and present its performance. This represents the first demonstration of online data selection in a LArTPC using real data and charge information exclusively and provides an important proof-of-principle for applying such techniques to other LArTPC experiments such as the Short-Baseline Near Detector and DUNE.

Abratenko, P. [Tufts U. (main)]↗

The real-time data processing and acquisition system for Project 8 Phase II

In Phase II of the Project 8 neutrino mass experiment, electrons from the decays of tritium or 83 m Kr are detected via their ≈ 26GHz cyclotron radiation while contained within a circular waveguide. The signal from a given electron is characterized as a brief chirp, lasting ≲ 10ms and changing in frequency by ≲ 1MHz/ms. To detect these signals, the Project 8 collaboration developed a Data Acquisition (DAQ) system tailored to the signal properties. The DAQ is responsible for simultaneously selecting up to three 100MHz-wide frequency windows to study, detect, and trigger on likely signals from different electron kinetic energies, and for writing the relevant data to disk. We describe the Phase II DAQ system in detail and address how the system was used for data-taking operations.

Ashtari Esfahani, A. [Washington U., Seattle; Shar↗

Improved Beam Loss Accounting with Fast Data Acquisition (DAQ) Chassis

Identifying the source of beam loss events in the CE-BAF accelerator can be a challenging task. However, with our new prototype system, this task becomes more effi-cient. The system, developed in the fall of 2022, utilizes a dispersive beam position monitor (BPM) and the exist-ing switched electrode electronics BPM hardware. Previ-ously a commercial off-the-shelf data acquisition (DAQ) system was employed to capture BPM wire signals at a sample rate of 20 kS/s. The fast shutdown signal triggered the system, which disables the beam at the injector. Analysis of beam position and energy variation before a beam loss event was used to determine if the beam loss event was associated with an energy transient. The proto-type system, implemented using National Instruments hardware and LabVIEW® software, relied on a software trigger. Manual post-processing was required to ascertain whether the fault was due to an un-tripped cavity with a gradient or phase transient. This work focuses on deploying a Fast DAQ Chassis to monitor BPM hardware in real time and during beam loss events. This system was originally developed and in-stalled in CEBAF to monitor the time-domain RF control signals in the legacy analog RF systems. This technology was leveraged to also monitor BPM signals. As the new system employs a hardware trigger, developing tools to automatically identify faults linked to energy transients unrelated to cavity faults will be straightforward. This paper will discuss the project's initial updates, underlin-ing the crucial role of each member of our team in this achievement

Tiskumara, J.↗

Search for e + e − → φ χ c 0 and φ η c 2 ( 1 D ) at center-of-mass energies from 4.47 to 4.95 GeV

Utilizing a dataset of 6.7 fb − 1 from electron-positron collisions recorded by the BESIII detector at the BEPCII storage ring, a search is conducted for the processes e + e − → ϕ χ c 0 and ϕ η c 2 ( 1 D ) across center-of-mass energies from 4.47 to 4.95 GeV. In the absence of any significant signals, upper limits are set. These include limits on the dressed cross sections for e + e − → ϕ χ c 0 , as well as the product of the dressed cross section for e + e − → ϕ η c 2 ( 1 D ) and a sum of five branching fractions. Furthermore, the product of the electronic width of Y ( 4660 ) and the branching fraction of the Y ( 4660 ) → ϕ χ c 0 , denoted as Γ e + e − Y ( 4660 ) B Y ( 4660 ) → ϕ χ c 0 , is determined to be < 0.35 eV at the 90% confidence level. Published by the American Physical Society 2025

Ablikim, M.↗

Evaluation of an event-driven 3FI ASIC for spectroscopic X-ray detection with synchrotron radiation

The novel design and evaluation on the NSLS-II beamline of the 3FI application-specific integrated circuit (ASIC) bump-bonded to a simple, planar, 2D segmented silicon sensor are presented. The ASIC was developed for full-field fluorescence spectral X-ray imaging (3FI). It is a small-scale prototype that features a square array of 32 × 32 pixels, and the size of the pixels is 100 µm × 100 µm. The ASIC was implemented in a 65 nm CMOS integrated circuit fabrication process. Each pixel incorporates a charge-sensitive amplifier, a shaping filter, a discriminator, a peak detector and a sample-and-hold circuit, allowing detection of events and storage of signal amplitudes. The system operates in a frameless event-driven readout mode, outputting analog values for threshold-triggered events, allowing high-speed multi-element X-ray fluorescence data acquisition. The 3FI ASIC achieves per-channel spectrometric performance at a power consumption of only 200 µW per pixel, with nearly all dissipation confined to the analog front-end. An energy resolution is measured at the level of 308 eV full width at half-maximum (FWHM) at 8.04 keV (Cu Kα), and 138 eV FWHM at 3.69 keV (Ca Kα). This per-pixel capability makes the prototype suitable for in situ trace element microanalysis in biological and environmental studies. Moreover, the frameless architecture of the detector is designed to address limitations of conventional X-ray fluorescence microscopy, which typically requires mechanical scanning, by enabling continuous high-throughput data acquisition in future full-field implementations.

47 OTHER INSTRUMENTATION↗

Emerging Jets Search, Triton Server Deployment, and Track Quality Development: Machine Learning Applications in High Energy Physics

Machine learning is becoming prevalent in high energy physics, with numerous applications in physics analyses and event reconstruction showing great improvements compared to traditional computing methods. This thesis studies three projects which each propose new avenues for machine learning applications within the high energy physics CMS experiment located at CERN. In the first project, a search for a dark matter signal called “emerging jets” is performed, using graph neural networks to greatly increase sensitivity to the signal’s signature within the data. The result of this dark matter search sets the most stringent exclusion limits to date on theoretical emerging jet models. Motivated by inefficiencies encountered when processing the emerging jet graph neural network at Fermi National Accelerator Laboratory’s computing centers, the second project re-optimizes the computing centers for machine learning inference. This re-optimization uses NVIDIA Triton Inference Servers to process users’ analysis code heterogeneously, therefore achieving high processing throughput and decreasing user time-to-insight. The last project focuses on an upgrade to the CMS experiment’s real-time event selection system which improves physics object reconstruction under harsh processing conditions. A boosted decision tree is used to quickly and efficiently quantify a reconstructed particle’s “track quality” in order to remove particle tracks reconstructed erroneously. In summary, this thesis will not only present examples of how high energy physics can greatly benefit by leveraging machine learning techniques for physics analysis and reconstruction, but will also provide guidance on how the field can prepare for the inevitable increase in machine learning applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Fluorescence Signatures of Rare Earth Metals during Precipitation in Various Conditions

Fluorescence spectroscopy is a widely used sensor methodology that analyzes light emitted from a compound or element as it decays from an excited state. This technique is very sensitive and selective, which is ideal to characterize analytes at lower limits of detection. Key example targets of significant industry and research interest include rare earth elements (REEs) such as dysprosium (Dy) and europium (Eu). These are widely used in advanced technologies including semiconductors, electric vehicle motors, lasers, and permanent magnets. Identifying new sources and responsible reutilization of REEs is essential, and new approaches to extract and recycle REEs could be notably enhanced through the integration of on-line sensors. The sensors can support faster process design, informed scale-up, and cost-effective deployment. This study covers the initial exploration of applying fluorescence-based on-line monitoring to REEs within a precipitation process. This study demonstrates the successful scale-up of a fluorescence -based sensing approach, from stationary cuvettes and small-volume microfluidic devices to continuous flow systems operating at the bench scale (10-25mL). This work also provides initial insight into the challenges of signal’s effects and utility within a turbid environment. Using a modular design for monitoring flowing solutions in a flow tube, fluorescence can be characterized for a variety of analytical targets. In this study, detection performance parameters between the cuvette and flow tube system were compared. Additionally, the response of Dy during precipitation by sodium bicarbonate in the two measurement designs was explored. This letter represents a starting point to bridge the gap between traditional fluorescence sensor measurements in a cuvette to future developments that explore the ability to integrate fluorescence sensors into extraction and separation processes at industrially relevant scales.

fluorescence↗

Precise measurement of the tt¯ production cross-section and lepton differential distributions in eμ dilepton events from s=13TeVpp collisions with the ATLAS detector

The inclusive top quark pair (tt¯$$t\bar{t}$$) cross-section σtt¯$$\sigma _{t\bar{t}}$$ has been measured in proton–proton collisions at s=13TeV$$\sqrt{s}=13\,\text {TeV}$$, using 140fb-1$$140\,{\text {fb}^{-1}} $$ of data collected by the ATLAS experiment at the Large Hadron Collider. Using events with an opposite-charge eμ$$e\mu $$ pair and b-tagged jets, the cross-section is measured to be: σtt¯=829.3±1.3(stat)±8.0(syst)±7.3(lumi)±1.9(beam)pb,$$\begin{aligned} \sigma _{t\bar{t}} & = 829.3\pm 1.3\,\mathrm {(stat)}\ \pm 8.0\,\mathrm {(syst)}\ \pm 7.3\,\mathrm {(lumi)}\ \\ & \quad \pm 1.9\,\mathrm {(beam)}\,\textrm{pb}, \end{aligned}$$where the uncertainties reflect the limited size of the data sample, experimental and theoretical systematic effects, the integrated luminosity, and the proton beam energy, giving a total uncertainty of 1.3%. The result is used to determine the top quark pole mass via the dependence of the predicted cross-section on mtpole$${m_{t}^\textrm{pole}}$$, giving mtpole=172.8-1.7+1.5$${m_{t}^\textrm{pole}}=172.8^{+1.5}_{-1.7}$$ GeV$$\text {GeV}$$. The same event sample is used to measure absolute and normalised differential cross-sections for the tt¯→eμνν¯bb¯$$t\bar{t} \rightarrow e\mu u \bar{ u }b\bar{b} $$ process as a function of single-lepton and dilepton kinematic variables. Complementary measurements of eμbb¯$$e\mu b\bar{b} $$ production, treating both tt¯$$t\bar{t}$$ and Wt events as signal, are also provided. Both sets of differential cross-sections are compared to the predictions of various Monte Carlo event generators, demonstrating that the state-of-the-art generators Powheg MiNNLO and Powhegbb4l describe the data better than Powheghvq.

Aad, G↗