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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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Using the Dynamic Networks Experiment 2 (DNE2) human-analyst event bulletin picks as a baseline signal detection dataset, we generate 47 additional datasets by gradually reducing their accuracy and completeness by randomly removing DNE2 picks, changing the initial phase labels from P to S and vice-versa, and injecting noise detections to simulate real-world signal detection algorithms.
Algorithms for radio frequency (RF) spectrum awareness need to be compatible with edge hardware to be practical for many applications. We developed a signal detection and classification model for the ZCU111 RF System-on-a-Chip (RFSoC) that operates on the fast Fourier transform of passband RF data. The system can detect and classify multiple signals of interest and display the predictions in real-time. The model consists of a modified ConvNeXt backbone and YOLOv3 head to operate on the Deep Learning Processing Unit on the RFSoC. We gathered datasets for training and testing by using a software defined radio to transmit example signals of Wi-Fi 802.11 b/g, Wi-Fi 802.11 n, FM Radio, LTE and LTE-M. By leveraging multiple inputs on the RFSoC frontend, the datasets span up to 4 GHz of bandwidth. The models showed high performance in classification accuracy, center frequency error, bandwidth error, and detection accuracy for both single and multi-signal datasets.
Draft of paper for the Journal of Dynamic Behavior of Materials
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Noble element detectors using argon or xenon as the detection medium are widely used in the searches for rare neutrino and dark matter interactions. Xenon doping in liquid argon can preserve attractive properties of an argon target while enhancing the detectable signals with properties of xenon. Here, in this work, we deployed a dual-phase liquid argon detector with up to 4% xenon doping in the liquid and studied its gas electroluminescence properties as a function of xenon concentration. At ∼2% xenon doping in liquid argon, we measured ∼34 ppm of xenon in the gas and observed ∼2.5 times larger electroluminescence signals using vacuum ultraviolet silicon photomultipliers than those in pure argon. Analysis of signals of different wavelengths confirms that the argon gas electroluminescence process is strongly modified by the addition of xenon. We propose an analytical model to describe the underlying energy transfer mechanism in argon-xenon gas mixtures. Lastly, the implications of this measurement for low-energy ionization signal detection will be discussed.
Recorded seismic data are generally contaminated by noise from different sources, which masks the signals of interest. In the seismology community, frequency filtering (FF) is the standard method for noise suppression. However, when the signal of interest and noise share the same frequency band, the latter cannot be filtered out without infringing on the former. We implemented a noise suppression approach based on the mathematical morphology theorem. The method involves compound operations of dilation and erosion using structuring elements of varying lengths and decomposes an input noisy waveform into several time functions with differing characteristics. Further, the filtered waveform is constructed from the time functions using a self-adaptive reconstruction technique. Application to a data set of >4700 local waveforms suggests that the implemented mathematical morphological filtering (MMF) approach is efficient for data with low signal-to-noise ratio (SNR) and significantly outperforms FF in that SNR range. For most of the dataset, FF, machine learning (ML) denoising, and continuous wavelet transform (CWT) thresholding result in higher SNR values compared with the MMF method. However, for ~42% of the waveforms, MMF outperforms FF, and the SNR gain achieved with MMF is as large as ~23 dB. Compared to ML denoising and CWT thresholding, this proportion drops to only ~10%–14%. Our results suggests that in an operational setting, MMF cannot replace the other noise suppression methods; however, signal detection can be improved if MMF is used to supplement them in some scenarios. MMF could help detect signals in problematic low-SNR data, which are currently being missed particularly when using FF alone.
Abstract Labile dissolved organic carbon in the surface oceans accounts for about one-fourth of carbon produced through photosynthesis and turns over on average every 3 days, fueling one of the largest engines of microbial heterotrophic production on the planet. Volatile organic compounds are poorly constrained components of dissolved organic carbon. Here, we detected 72 m/z signals, corresponding to unique volatile organic compounds, including petroleum hydrocarbons, totaling ~18.5 nM in the culture medium of a model diatom. In five cocultures with bacteria adapted to grow with this diatom, 1–59 m/z signals were depleted. Two of the most active volatile organic compound consumers, Marinobacter and Roseibium, contained more genes encoding volatile organic compound oxidation proteins, and attached to the diatom, suggesting volatile organic compound specialism. With nanoscale secondary ion mass spectrometry and stable isotope labeling, we confirmed that Marinobacter incorporated carbon from benzene, one of the depleted m/z signals detected in the co-culture. Diatom gross carbon production increased by up to 29% in the presence of volatile organic compound consumers, indicating that volatile organic compound consumption by heterotrophic bacteria in the phycosphere—a region of rapid organic carbon oxidation that surrounds phytoplankton cells—could impact global rates of gross primary production.
We present a mechanism that allows thermal relic dark matter to annihilate efficiently in the Galactic Halo and in galaxy clusters, but not in the lower-velocity environments of dwarf spheroidal (dSph) galaxies. We realize this within a complete model in which the dark matter consists of two distinct states separated by a small mass splitting. An indirect detection signal is generated only through the coannihilations of these two states, requiring both to be present. In the halo of the Milky Way, the dark matter particles in the lighter state can be excited into the long-lived heavier state through scattering. Once excited, these heavier particles can coannihilate with those in the lighter state, yielding a gamma-ray signal with little or no suppression. By contrast, the dark matter particles in dwarf galaxies do not possess enough kinetic energy to be excited, thereby suppressing the coannihilation rate and corresponding indirect detection signals from those systems. This framework breaks the predictive relationship that ordinarily exists between these respective gamma-ray signals and complicates our ability to interpret the results of indirect detection searches.
Researchers from a broad spectrum of scientific and engineering disciplines are increasingly using scattering-type near-field infrared spectroscopic techniques to characterize materials non-destructively with nanoscale spatial resolution. However, a sub-optimal understanding of a technique's implementation can complicate data interpretation and act as a barrier to entering the field. Here the key detection and processing steps involved in producing scattering-type near-field nanoscale Fourier transform infrared spectra (nano-FTIR) are outlined. The self-contained mathematical and experimental work derives and explains: i) how normalized complex-valued nano-FTIR spectra are generated, ii) why the real and imaginary components of spectra qualitatively relate to dispersion and absorption respectively, iii) a new and generally valid equation for spectra which can be used as a springboard for additional modeling of the scattering processes, and iv) an algebraic expression that can be used to extract an approximation to the sample's local extinction coefficient from nano-FTIR. The algebraic model for weak oscillators is validated with nano-FTIR and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra on samples of polystyrene and Kapton and further provides a pedagogical pathway to cementing some of the technique's key qualitative attributes.
We identify symmetries in a broad class of vectorlike confining dark sectors that forbid the leading electromagnetic moments that would ordinarily mediate dark baryon scattering with the Standard Model. The absence of these operators implies dark baryon dark matter has much smaller cross sections for elastic scattering off nuclei, leading to suppressed direct detection signals. In the confined description, we identify an “ℋ-parity” symmetry that exists in any dark sector with dark quarks transforming under a vectorlike representation of a new confining SU(𝑁 𝑐 ) gauge theory as well as a vectorlike representation of the electroweak group SU(2) 𝐿 . The parity is independent of 𝑁 𝑐 and 𝑁 𝑓 , though it is essential that the dark quarks are neutral under hypercharge. This parity forbids dark hadron electric and magnetic dipole moments, charge radius, and anapole moment, while permitting dimension-7 operators that include polarizability, electroweak loop-induced interactions, and lower-dimensional electromagnetic transition moments between different neutral dark baryon states. We work out an explicit example, 𝑁 𝑐 = 𝑁 𝑓 = 3, that is the most minimal theory with fermionic dark baryons. In this specific model, we use the nonrelativistic quark model to show the magnetic dipole moment and charge radius vanish, while the transition moments are nonzero, consistent with ℋ-parity. We discuss the implications of a suppressed direct detection signal, emphasizing that this broad class of models provide a well-motivated target for future colliders.
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Abstract Among the various observational techniques used for the detection of large bolides on a global scale is a low-frequency sound known as infrasound. Infrasound, which is also one of the four sensing modalities used by the International Monitoring System, offers continuous global monitoring and can be leveraged for planetary defense. Infrasonic records can provide an additional dimension for event characterization and a distinct perspective that might not be available through any other observational method. This paper describes the infrasonic detection and characterization of the bolide that disintegrated over Tajikistan on 2008 July 23. This event was detected by two infrasound stations at distances of 1530 and 2130 km. Propagation paths to one of the stations were not predicted by the model, despite being clearly detected. The presence of the signal is attributed to the acoustic energy being trapped in a weak but leaky stratospheric AtmoSOFAR channel. The infrasound signal analysis indicates that the shock originated at the point of the main breakup at an altitude of 35 km. The primary mode of the shock production of the signal detected at the two stations was a spherical blast resulting from the main gross fragmentation episode. The energy estimate, based on the signal period, is 0.17–0.51 kt of TNT equivalent, suggesting a mass of 6.6–23.5 tons. The corresponding object radius, assuming the chondritic origin, was 0.78–1.18 m.
A method for modeling light transport through a scattering medium prior to being incident on a detector and a corresponding system is disclosed. The method determines the effects of scattering and absorption caused by particles as a function of the density, size, and refractive index of the particles, as well as the wavelength of the light source. Based on the determined scattering and absorption coefficients, the signal incident on the detector may be calculated. The calculation may also be inverted such that based upon the detected signal, an object may be detected, and its location in the scattering medium may be estimated.
Gravitational waves emitted after neutron star binary coalescences and the information they carry about dense matter are a high-priority target for next-generation detectors. Even though such detectors are expected to observe millions of signals, detectable postmerger emission will remain rare. Here, in this work, we explore postmerger detectability and inference through an alternative detector readout scheme for data dominated by quantum-noise, which is the case above 1 kHz; photon-counting. In such a readout, signals and noise become quantized into discrete distributions corresponding to the detection of single photons measured in a chosen basis of modes. Through simulated data, we demonstrate that photon counting can be efficient even for weak signals. We find ∼1 in 100 signals with a postmerger signal-to-noise ratio of 0.2 can result in a single photon and thus be detected. Furthermore, after 2 ×10 4 signals—equivalent to 10 −2 to 1.5 years of observation—photon counting results in a twofold improvement in the measurement of the radius of a 1.6𝑀 ⊙ neutron star. Constraints can be further tightened if the detector classical noise is reduced. Photon counting offers a promising alternative to traditional homodyne readout techniques for extracting information from low signal-to-noise ratio postmerger signals.
Rationale Signal detection for uranium–lead (U–Pb) dating of zircon is typically performed via ion counters. Here, we develop a preliminary understanding of the strengths and limitations of faraday‐cup‐based detection. Methods A suite of zircon reference materials and the NIST‐610 glass were sampled using laser ablation followed by U–Pb isotope ratio measurement on a Neoma multicollector‐inductively coupled plasma‐mass spectrometer. Results We were able to produce geologically accurate 207 Pb/ 206 Pb, 206 Pb/ 238 U, and 207 Pb/ 235 U ratios for the NIST‐610 glass and the zircon standards, with ages ranging from ~2.5 Ga to ~337 Ma (TanBrown A, Oracle, 91550, Mud Tank, Temora, and Plešovice). Two of the younger zircon standards examined (94‐35, ~55.6 Ma, and Fish Canyon, 28.6 Ma) yielded accurate 206 Pb/ 238 U but not 207 Pb/ 235 U or 207 Pb/ 206 Pb ratios, whereas the youngest zircon standard (Penglai, ~4.4 Ma) failed for all three ratios of interest. The accuracy and precision of the all‐faraday method are directly tied to signal intensity, with reliable data capable of being produced even when both isotopes in a ratio have signals below ~0.001 V (equivalent to ~62 500 cps on an ion counter). Conclusion The all‐faraday cup multicollection method provides sufficient sensitivity to obtain geologically meaningful U–Pb data, with possible advantages being that laser pit depth‐dependent changes in the observed interelemental fractionation behavior may be easier to correct using a static collector configuration compared to when the ion beam is swept across a single detector while also removing the need for an interdetector‐type calibration. Further work is needed to refine the all‐faraday cup method (e.g., application of background subtraction and common Pb corrections, outlier removal, and interelement as well as down‐hole fractionation corrections), but our initial results demonstrate that the faraday detector method has sufficient sensitivity to warrant further study.
The dual-phase xenon time projection chamber (TPC) is a powerful technology to detect rare interactions such as scatters of dark matter particles on nuclei. In particular, the built-in gain of ionization signals in a dual-phase TPC makes it sensitive to events in the few-electron regime, as expected from low-mass dark matter interactions. The pursuit of this low-energy sensitivity through ionization-only signal detection has so far been hindered by excessive electron backgrounds observed across experiments. Much of this background is attributed to the plate-out of $^{222}$Rn decay chain isotopes on the high voltage electrode grid surfaces that span the full cross section of the TPC. This work presents a first-principle model constructed for this background, the predictions of which are consistent with data from the LZ and LUX experiments. We then discuss mitigation strategies of this background in future dual-phase TPCs and the possibility of applying this grid background model to ionization-only dark matter searches.
We present a search for boosted dark matter from primordial black hole (PBH) evaporation using the DarkSide-50 ionization-signal-only dataset corresponding to the experiment’s ( 12202 ± 180 ) kg d exposure. We focus on evaporation of PBHs with masses in the range [ 10 14 , 10 16 ] g producing Dirac fermionic dark matter particles with sub-GeV kinetic energy. These relativistic particles, with energies up to hundreds of MeV, can generate detectable signals for masses below O ( 100 ) MeV . The absence of a signal enables setting complementary limits to those derived from cosmological observations and direct detection searches for cosmic-ray-boosted dark matter.