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At least 415 records · Page 23

Sparse distributed memory overview

The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.

Raugh, Mike↗

Kernel PLS-SVC for Linear and Nonlinear Discrimination

A new methodology for discrimination is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by support vector machines for classification. Close connection of orthonormalized PLS and Fisher's approach to linear discrimination or equivalently with canonical correlation analysis is described. This gives preference to use orthonormalized PLS over principal component analysis. Good behavior of the proposed method is demonstrated on 13 different benchmark data sets and on the real world problem of the classification finger movement periods versus non-movement periods based on electroencephalogram.

Rosipal, Roman↗

Quantum Time Dynamics Mediated by the Yang–Baxter Equation and Artificial Neural Networks

Quantum computing shows great potential, but errors pose a significant challenge. This study explores new strategies for mitigating quantum errors using artificial neural networks (ANNs) and the Yang–Baxter equation (YBE). Unlike traditional error mitigation methods, which are computationally intensive, we investigate artificial error mitigation. We developed a novel method that combines ANNs for noise mitigation combined with the YBE to generate noisy data. This approach effectively reduces noise in quantum simulations, enhancing the accuracy of the results. The YBE rigorously preserves quantum correlations and symmetries in spin chain simulations in certain classes of integrable lattice models, enabling effective compression of quantum circuits while retaining linear scalability with the number of qubits. This compression facilitates both full and partial implementations, allowing the generation of noisy quantum data on hardware alongside noiseless simulations using classical platforms. By introducing controlled noise through the YBE, we enhance the data set for error mitigation. We train an ANN model on partial data from quantum simulations, demonstrating its effectiveness in mitigating errors in time-evolving quantum states, providing a scalable framework to enhance quantum computation fidelity, particularly in noisy intermediate-scale quantum (NISQ) systems. We demonstrate the efficacy of this approach by performing quantum time dynamics simulations using the Heisenberg XY Hamiltonian on real quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian analysis of nucleon-nucleon scattering data in pionless effective field theory

We perform Bayesian model calibration of two-nucleon (NN) low-energy constants (LECs) appearing in an NN interaction based on pionless effective field theory (πEFT). The calibration is carried out for potentials constructed using naive dimensional analysis in NN relative momenta (p) up to next-to-leading order [NLO, O(p 2 )] and next-to-next-to-next-to-leading order [N3LO, O(p 4 )]. We consider two classes of pionless πEFT potential: one that acts in all partial waves and another that is dominated by s-wave physics. The two classes produce broadly similar results for calibrations to NN data up to E lab = 5 MeV. Our analysis accounts for the correlated uncertainties that arise from the truncation of the pionless πEFT. We simultaneously estimate both the πEFT LECs and the parameters that quantify the truncation error. This permits the first quantitative estimates of the pionless πEFT breakdown scale, Λ b : the 95% intervals are Λ b ∈[50.11,63.03] MeV at NLO and Λ b ∈[72.27,88.54] MeV at N3LO. Furthermore, invoking naive dimensional analysis for the NN potential, therefore, does not lead to consistent results across orders in pionless πEFT. This exemplifies the possible use of Bayesian tools to identify inconsistencies in a proposed EFT power counting.

Bayesian methods↗

Different model assumptions about plant hydraulics and photosynthetic temperature acclimation yield diverging implications for tropical forest gross primary production under warming

Tropical forest photosynthesis can decline at high temperatures due to (1) biochemical responses to increasing temperature and (2) stomatal responses to increasing vapor pressure deficit (VPD), which is associated with increasing temperature. It is challenging to disentangle the influence of these two mechanisms on photosynthesis in observations, because temperature and VPD are tightly correlated in tropical forests. Nonetheless, quantifying the relative strength of these two mechanisms is essential for understanding how tropical gross primary production (GPP) will respond to climate change, because increasing atmospheric CO 2 concentration may partially offset VPD-driven stomatal responses, but is not expected to mitigate the effects of temperature-driven biochemical responses. We used two terrestrial biosphere models to quantify how physiological process assumptions (photosynthetic temperature acclimation and plant hydraulic stress) and functional traits (e.g., maximum xylem conductivity) influence the relative strength of modeled temperature versus VPD effects on light-saturated GPP at an Amazonian forest site, a seasonally dry tropical forest site, and an experimental tropical forest mesocosm. By simulating idealized climate change scenarios, we quantified the divergence in GPP predictions under model configurations with stronger VPD effects compared with stronger direct temperature effects. Assumptions consistent with stronger direct temperature effects resulted in larger GPP declines under warming, while assumptions consistent with stronger VPD effects resulted in more resilient GPP under warming. Furthermore, our findings underscore the importance of quantifying the role of direct temperature and indirect VPD effects for projecting the resilience of tropical forests in the future, and demonstrate that the relative strength of temperature versus VPD effects in models is highly sensitive to plant functional parameters and structural assumptions about photosynthetic temperature acclimation and plant hydraulics.

54 ENVIRONMENTAL SCIENCES↗

Variable Daily Autocorrelation Functions of High-Frequency Seismic Data on Mars

Abstract High-frequency seismic data on Mars are dominated by wind-generated lander vibrations, which are radiated partially to the subsurface. Autocorrelation functions (ACFs) of seismic data on Mars filtered between 1 and 5 Hz show clear phases at ∼1.3, ∼2.6, and ∼3.9 s. Daily temporal changes of their arrival times (dt/t) correlate well with the daily changes of ground temperature, with ∼5% daily variation and ∼50 min apparent phase delay. The following two mechanisms could explain the observations: (1) the interference of two predominant spectral peaks at ∼3.3 and ∼4.1 Hz, assumed to be both lander resonance modes, generate the apparent arrivals in the ACFs; (2) the interference of the lander vibration and its reflection from an interface ∼200 m below the lander generate the 3.3 Hz spectral peak and ∼1.3 s arrival in the ACFs. The driving mechanism of the resolved dt/t that most likely explains the ∼50 min delay is thermoelastic strain at a near-surface layer, affecting the lander–ground coupling and subsurface structures. The two outlined mechanisms suggest, respectively, up to ∼10% changes in ground stiffness at 1–5 Hz and ∼15% velocity changes in the top ∼20 m layer. These are upper bound values considering also other possible contributions. The presented methodology and results contribute to analysis of ACFs with limited data and the understanding of subsurface materials on Mars.

Geochemistry & Geophysics↗

Tritium Trapping Thermodynamics by Point Defects at Interfacial Fe-Al Phases of the Aluminide Coating

Density functional theory (DFT) simulations have been carried out to evaluate the potential for tritium trapping by metal vacancies in four phases (i.e., (Fe, Cr, Ni), AlFe 3 , NiAl, and AlFe) identified near the interface between the Al coating and 316 stainless steel (316 SS) cladding. In addition, an ab initio thermodynamics approach has been employed to predict the temperature and T 2 -partial pressure dependence on the thermodynamics of tritiated defects. Key results in this work suggest that metal vacancies in the four phases have the potential to favorably trap tritium species. This thermodynamic trend can be correlated to the high energy cost of having an interstitial tritium in the lattice, which has been calculated to be at least 0.48 eV. By combining the results of this study with previous theoretical works investigating tritium behavior in other Fe-Al phases identified in the aluminide coating, suggest that metal vacancies are generally able to trap tritium in various Fe-Al aluminide phases. Especially, it was found that Al vacancies are the most efficient to trap tritium, followed by Fe vacancies, then Ni and Cr vacancies. Strong interactions between tritium and the metal vacancies are occurring by the formation of Fe—T bonds. The formation of Cr—T, Ni—T, or Al—T bonds are found less energetically favorable than Fe—T bonds.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Site Occupancy Preference and Magnetic Properties in Nd 2 (Fe,Co) 14 B

Partial replacement of Fe by Co is an effective method to increase Curie temperature (T C ) , which improves the thermal stability of magnetic properties in Nd 2 Fe 14 B-based permanent magnets. The correlation between Fe substitution and magnetic properties has been studied in Nd 2 (Fe,Co) 14 B via a first-principles calculation. The calculated Fe substitution energies indicate that the Co atoms avoid the 8 j 2 site, which agrees with the experiments. The Co atoms are ferromagnetically coupled with Fe sublattice and show magnetic moments of about 1.2 to 1.7 μ B at different crystallographic sites, less than that of Fe (2.1–2.7 μ B ), resulting in the decrease in total magnetization at ground state (0 K) with increasing Co content. The effective exchange interaction parameter, derived from the energy difference between varied magnetic structures, increases from 7.8 meV to 17.0 meV with increasing Co content from x = 0 to x = 14 in Nd 2 Fe 14–x Co x B. This change in the effective exchange interaction parameter is responsible for the enhancement of T C in Nd 2 (Fe,Co) 14 B. The total magnetization at 300 K, derived from mean-field theory, shows a peak maximum value at x = 1 in Nd 2 Fe 14–x Co x B. The phenomenon results from the interplay between the reduction of the magnetic moment in the Fe(Co) sublattice and the enhancement of T C with increasing Co content.

36 MATERIALS SCIENCE↗

Nitridation of silicon

Silicon powders with three levels of impurities, principally Fe, were sintered in He or H2. Non-densifying mechanisms of material transport were dominant in all cases. High purity Si showed coarsening in He while particle growth was suppressed in H2. Lower purity powder coarsened in both He and H2. The same three Si powders and Si /111/ single crystal wafers were nitrided in both N2 and N2/H2 atmospheres. Hydrogen increased the degree of nitridation of all three powders and the alpha/beta ratio of the lower purity powder. Some Si3N4 whiskers and open channels through the surface nitride layer were observed in the presence of Fe, correlating with the nitridation-enhancing effects of Fe. Thermodynamic calculations showed that when SiO2 is present on the Si, addition of H2 to the nitriding atmosphere decreases the amount of SiO2 and increases the partial pressure of Si-containing vapor species, that is, Si and SiO. Large amounts of NH3 and SiH4 were also predicted to form.

Shaw, N. J.↗

Changes in chemical and optical properties of thin film metal mirrors on LDEF

Thin films of the metals Cu, Ni, Pt, Au, Sn, Mo, and W deposited on fused silica flats were exposed at ambient temperature on the leading and trailing faces of the LDEF. Reflectances of these films were measured from 250 to 2500 nm and compared with controls. The exposed films were subjected to the LDEF external environment including atomic oxygen, molecular contamination, and solar ultraviolet. Major changes in optical and infrared reflectance were seen for Cu, Mo, Ni, and W films on the leading face of LDEF and are attributed to partial conversion of metal to metal oxide. Smaller changes in optical properties are seen on all films and are probably caused by thin contaminant films deposited on top of the metal. The optical measurements are correlated with film thickness measurements, x-ray photoelectron spectroscopy, optical calculations, and, in the case of Cu, with x-ray diffraction measurements. In a few cases, comparisons with results from a similar UAH experiment on STS-8 have been drawn.

Peters, Palmer N.↗

Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval

In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March–April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial–temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations.

Lu Zhou↗

Understanding the Electronic Behavior of f-Element Intermetallics

Due to their partially filled f-orbitals, lanthanide and actinide intermetallic materials exhibit intriguing electronic, structural, and magnetic properties. These materials provide a unique platform to explore exotic magnetic and quantum phenomena that arise from their strongly correlated f-electrons, offering insights into f-electron behavior. Incorporating light elements such as boron and carbon can significantly impact the electronic, chemical, and physical properties of these materials, with varying influence between lanthanides and actinides due to the more localized f-electrons in lanthanides. In this work, lanthanide-based intermetallic single crystals containing light atoms were synthesized using the molten metal flux growth method. In this method, one or more low-melting metals such as aluminum, gallium, tin, and bismuth are used in excess as the reaction medium. This solution-state approach allows for lower reaction temperatures compared to solid-state reactions and enables the isolation of kinetic products rather than thermodynamically stable compounds. The synthesized crystals were analyzed using an extensive array of analytical and computational characterization techniques, including single crystal X-ray diffraction, scanning electron microscopy, energy-dispersive spectroscopy, magnetization measurements, and density functional theory calculations. These analyses provided detailed insights into the structural and magnetic properties of the synthesized materials.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Radiative lifetime-encoded unicolour security tags using perovskite nanocrystals

Traditional fluorescence-based tags, used for anticounterfeiting, rely on primitive pattern matching and visual identification; additional covert security features such as fluorescent lifetime or pattern masking are advantageous if fraud is to be deterred. Herein, we present an electrohydrodynamically printed unicolour multi-fluorescent-lifetime security tag system composed of lifetime-tunable lead-halide perovskite nanocrystals that can be deciphered with both existing time-correlated single-photon counting fluorescence-lifetime imaging microscopy and a novel time-of-flight prototype. We find that unicolour or matching emission wavelength materials can be prepared through cation-engineering with the partial substitution of formamidinium for ethylenediammonium to generate “hollow” formamidinium lead bromide perovskite nanocrystals; these materials can be successfully printed into fluorescence-lifetime-encoded-quick-read tags that are protected from conventional readers. Furthermore, we also demonstrate that a portable, cost-effective time-of-flight fluorescence-lifetime imaging prototype can also decipher these codes. A single comprehensive approach combining these innovations may be eventually deployed to protect both producers and consumers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sequence-specific dynamic DNA bending explains mitochondrial TFAM’s dual role in DNA packaging and transcription initiation

Abstract Mitochondrial transcription factor A (TFAM) employs DNA bending to package mitochondrial DNA (mtDNA) into nucleoids and recruit mitochondrial RNA polymerase (POLRMT) at specific promoter sites, light strand promoter (LSP) and heavy strand promoter (HSP). Herein, we characterize the conformational dynamics of TFAM on promoter and non-promoter sequences using single-molecule fluorescence resonance energy transfer (smFRET) and single-molecule protein-induced fluorescence enhancement (smPIFE) methods. The DNA-TFAM complexes dynamically transition between partially and fully bent DNA conformational states. The bending/unbending transition rates and bending stability are DNA sequence-dependent—LSP forms the most stable fully bent complex and the non-specific sequence the least, which correlates with the lifetimes and affinities of TFAM with these DNA sequences. By quantifying the dynamic nature of the DNA-TFAM complexes, our study provides insights into how TFAM acts as a multifunctional protein through the DNA bending states to achieve sequence specificity and fidelity in mitochondrial transcription while performing mtDNA packaging.

59 BASIC BIOLOGICAL SCIENCES↗

Time scales for nonlinear processes in preheating after multifield inflation with nonminimal couplings

We have conducted extensive lattice simulations to study the postinflation dynamics of multifield models involving nonminimal couplings. In this work, we explore the parameter dependence of preheating in these models and describe the various time scales that control such nonlinear processes as energy transfer, rescattering, and the approach to radiation domination and thermalization. In the limit of large nonminimal couplings ($ξ_I$ ~ 100), we find that efficient transfer of energy from the inflaton condensate to radiative degrees of freedom, emergence of a radiation-dominated equation of state, and the onset of thermalization each consistently occur within $N_{\text{reh}} ≲ 3 e$-folds after the end of inflation, largely independent of the values of the other couplings in the models. The exception is the case of negative ellipticity, in which there is a misalignment between the dominant direction in field space along which the system evolves and the larger of the nonminimal couplings $ξ_I$. In those cases, the field-space-driven parametric resonance is effectively shut off. More generally, the competition between the scalar fields’ potential and the field-space manifold structure can yield interesting phenomena such as two-stage resonances. Across many regions of parameter space, we find efficient re-scattering between the distinct fields, leading to a partial memory loss of the shape of the initial fluctuation spectrum. Despite the explosive particle production, which can lead to a quick depletion of the background energy density, the nonlinear processes do not induce any superhorizon correlations after the end of inflation in these models, which keeps predictions for cosmic microwave background observables unaffected by the late-time amplification of isocurvature fluctuations. Hence the excellent agreement between primordial observables and recent observations is preserved for this class of models, even when we consider postinflation dynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Entanglement Benchmarking in Quantum Simulations of Spin Systems

We simulate quantum spin systems and measure entanglement using circuits tailored for near-term quantum computers. Traditional tools like entanglement entropy are limited to pure states and require full state tomography, making them impractical on current hardware. Instead, we employ the novel approach, Positive Partial Transpose (PPT) criterion to efficiently detect pairwise entanglement from two-spin reduced density matrices, applicable to both pure and mixed states. This method enables scalable entanglement detection, providing a practical route to study quantum correlations, phase transitions, and benchmark quantum devices.

Baul, Anshumitra [ORNL] (ORCID:0000000268947191)↗

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks [Slides]

This presentation discusses Nuclear Criticality Safety (NCS) and how designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear experiments. The presentation poses the question of how this analysis can be performed and states that the answer lies in matching new nuclear experiments with existing benchmark experiments using similarity metrics. By increasing the criticality safety of the application in this work, higher mass limits could be used in PF-4 operations. Additionally, the presentation discusses MCNP6.2®, Whisper-1.1, the software that can be used in this analysis. Also discussed is the fact that International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks rarely match new nuclear applications and that there are significant differences in given set of materials and/or geometry. If there are no benchmarks that match the application, the presentation discusses the possibility of creating new benchmarks. In conclusion, this work presents a Gaussian process (GP) optimization scheme that was used to generate new benchmarks with the highest sensitivity-based similarity metrics to user-defined nuclear applications. The Gaussian process optimization successfully designed 3 new experimental benchmarks that were highly correlated to the application of interest and had k eff values near critical. Optimization over c k,i-r has shown that investigating specific isotope reactions for different applications is crucial to designing benchmark experiments. Partial contribution from Pu dominates c k similarity metric. Future work includes testing new stand-alone similarity metrics or new combinations of similarity metrics as the design criterion of this optimization – design criterion is application dependent.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Infrared spectra of protostars - Composition of the dust shells

Nearly complete 2 to 13 micron spectra are presented for 13 compact infrared sources associated with molecular clouds, along with partial spectra of six additional objects. The spectra are found to resemble blackbodies with superposed absorption features from 2.8 to 3.5 microns, at 6.0 and 6.8 microns, and in the silicate band centered near 9.7 microns. Correlations among the features are investigated in an attempt to confirm possible identifications. A good correlation between the deepest part of the absorption at 3.1 microns, its long wavelength wing, and the 6.0 micron features suggests that all may derive from large amorphous water ice particles. The relatively poor correlation between the 3.4 and 6.8 micron optical depths adds no evidence in support of the suggestion that these bands may be due to CH bonds

Willner, S. P.↗