Rare Event Sampling Improves Mercury Instability Statistics
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This paper describes an efficient technique for estimating, via simulation, the probability of buffer overflows in a queueing model that arises in the analysis of ATM (Asynchronous Transfer Mode) communication switches. There are multiple streams of (autocorrelated) traffic feeding the switch that has a buffer of finite capacity. Each stream is designated as either being of high or low priority. When the queue length reaches a certain threshold, only high priority packets are admitted to the switch's buffer. The problem is to estimate the loss rate of high priority packets. An asymptotically optimal importance sampling approach is developed for this rare event simulation problem. In this approach, the importance sampling is done in two distinct phases. In the first phase, an importance sampling change of measure is used to bring the queue length up to the threshold at which low priority packets get rejected. In the second phase, a different importance sampling change of measure is used to move the queue length from the threshold to the buffer capacity.
Earlier studies based on a single solar cycle had resulted in a sharp division of events into 'ordinary' and 'anomalously large' events. Two such entirely separate distributions imply two entirely separate acceleration mechanisms, one common and the other very rare. The sharp division is neither required nor justified by this larger sample. Instead the event intensity forms a smooth distribution for intensities up to the largest observed implying that any second acceleration mechanism cannot be rare. Also, a clear bimodal variation of annual integrated flux with solar cycle phase but no statistically significant tendency for the large events to avoid sunspot maximum is found. There is almost no relation between the maximum sunspot number in a solar cycle and the solar cycle integrated flux. It is also found that for annual sunspot numbers greater than 35 there is no relation whatsoever between the annual sunspot numbers and annual integrated flux.
It is noted that the variable Rb-Sr model ages of lunar highland rocks containing a significant amount of KREEP basalt may be best explained by some fractionation of Rb from Sr during metamorphism 3.9 billion years ago, but the uniformity of the KREEP-type trace-element pattern in different highland samples indicates that elements such as the rare earth were hardly fractionated at all during the metamorphic event. Data are presented which show that the Rb/Sr fractionation 3.9 billion years ago was due to Rb mobilization alone in most cases and that this fractionation can be accounted for by coupling of Rb to other, less volatile incompatible elements. Variations of Rb in lunar highland rocks are analyzed, a correction method is applied for the Rb/Sr fractionation, and results are evaluated separately for Apollo 16 VHA and KREEP basalts, Apollo 17 noritic breccias, Apollo 14 KREEP breccias, Apollo 15 KREEP basalts, and Apollo 15-KREEP-enriched breccias. Evidence for volatilization of alkalis from glasses of impact origin is summarized, and an apparent correlation is discussed between meteoritic component (as given by the Ir/Au ratio) and rock type (as given by the U or Rb content) for many lunar highland samples.
The possibility that certain very young meteorites originated as impact melts on a large asteroid or asteroids is investigated. Calculations of the thermal evolution of impact melt show that the solidification time should be long enough to produce igneous or quasi-cumulate textures within rocks if the crater is large enough and if the initial clast concentration is low, at least in some portion of the melt sheet. The number of collisions within the asteroid belt which would produce craters of the requisite size is calculated. Using an estimate of the current size distribution of asteroids, it is found that over 3000 such collisions should have occurred during the lifetime of the solar system. Excavation and ejection of the solidified melt by a subsequent impact would be dynamically easy because of the low escape velocities of even the largest asteroids but improbable because of the depth that must be sampled. A second, sufficiently large impact is rare, so only the products of one such double event have been obtained up to now.
Ar-39 - Ar-40 analyses of three petrographically distinct, shocked Apollo 15 KREEP (i.e., high K, rare earth element, P, and other trace element contents) basalt samples demonstrate that a major impact event affected all three samples at about 2.1 Ga. The Copernican System craters Aristillus and Autolycus are to the north. Autolycus, the older of the two, is in a particularly appropriate terrain and is the most likely source of the 2.1 Ga heating and delivery event. With this calibration point, and if Autolycus really is a Copernican crater, the Copernican System lasted twice as long as has previously been suggested. Furthermore, the moon was not subjected to a constant cratering rate over the past 3 billion years; the average rate in the preceding Eratosthenian must have been twice that in the Copernican.
Statistical thinking permeates many important decisions as NASA plans its Quesst mission, which will culminate in a series of community overflights using the X-59 aircraft to demonstrate low-noise supersonic flight. Month-long longitudinal surveys will be deployed to assess human perception and annoyance to this new acoustic phenomenon. NASA works with a large contractor team to develop systems and methodologies to estimate noise doses, to test and field socio-acoustic surveys, and to study the relationship between the two quantities, dose and response, through appropriate choices of statistical models. This latter dose-response relationship will serve as an important tool as national and international noise regulators debate whether overland supersonic flights could be permitted once again within permissible noise limits. In this presentation we highlight several areas where statistical thinking has come into play, including issues of sampling, classification and data fusion, and analysis of longitudinal survey data that are subject to rare events and the consequences of measurement error. We note several operational constraints that shape the appeal or feasibility of some decisions on statistical approaches, and we identify several important remaining questions to be addressed.
Radioactive rare gases and tritium in Apollo 12 lunar rocks and in sample return container, noting relationship to solar flare event
The correlated distributions of satellite-measured visible and infrared radiances, caused by spatial and temporal variations in clouds and surfaces, have been found to be characteristic of the major climate regimes and can be described by the attributes of bidimensional and monodimensional histograms and time-composite images. Most of the variability of both the surfaces and clouds is found to occur at scales larger than the minimum resolved by satellite imagery. Since satellite imaging data sets are difficult to analyze because of their large volumes, many studies reduce the volume by various sampling or averaging schemes. The effects of data resolution and sampling on the radiance histogram statistics and on the time-composite image characteristics are examined. In particular, the sampling strategy used by the International Satellite Cloud Climatology Project is tested. This sampling strategy is found to preserve the statistics of smaller cloud variations for most regions, with the exception of very rare events, if they are accumulated over large enough areas (at least 500 km in dimension) and long enough time periods (at least one month).
This work deals with the challenge of online adaptive data collection in a time series. A remote sensor or explorer agent adapts its rate of data collection in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility (all its datapoints lie in the past) and limited control (it can only decide when to collect its next datapoint). This problem is treated from an information-theoretic perspective, fitting a probabilistic model to collected data and optimizing the future sampling strategy to maximize information gain. The performance characteristics of stationary and nonstationary Gaussian process models are compared. Self-throttling sensors could benefit environmental sensor networks and monitoring as well as robotic exploration. Explorer agents can improve performance by adjusting their data collection rate, preserving scarce power or bandwidth resources during uninteresting times while fully covering anomalous events of interest. For example, a remote earthquake sensor could conserve power by limiting its measurements during normal conditions and increasing its cadence during rare earthquake events. A similar capability could improve sensor platforms traversing a fixed trajectory, such as an exploration rover transect or a deep space flyby. These agents can adapt observation times to improve sample coverage during moments of rapid change. An adaptive sampling approach couples sensor autonomy, instrument interpretation, and sampling. The challenge is addressed as an active learning problem, which already has extensive theoretical treatment in the statistics and machine learning literature. A statistical Gaussian process (GP) model is employed to guide sample decisions that maximize information gain. Nonsta tion - ary (e.g., time-varying) covariance relationships permit the system to represent and track local anomalies, in contrast with current GP approaches. Most common GP models are stationary, e.g., the covariance relationships are time-invariant. In such cases, information gain is independent of previously collected data, and the optimal solution can always be computed in advance. Information-optimal sampling of a stationary GP time series thus reduces to even spacing, and such models are not appropriate for tracking localized anomalies. Additionally, GP model inference can be computationally expensive.
Focusing on undesired operator behaviors is pervasive in system design and safety management cultures in aviation. This focus limits the data that are collected, the questions that are asked during data analysis, and therefore our understanding of what operators do in everyday work. Human performance represents a significant source of aviation safety data that includes both desired and undesired actions. When safety is characterized only in terms of errors and failures, the vast majority of human impacts on system safety and performance are ignored. The outcomes of safety data analyses dictate what is learned from those data, which in turn informs safety policies and safety-related decision making. When learning opportunities are systematically restricted by focusing only on rare failure events, not only do we learn less (and less often), but we can draw misleading conclusions by relying on a non-representative sample of human performance data. Changes in how we define and think about safety can highlight new opportunities for collection and analysis of safety-relevant data. Developing an integrated safety picture to better inform safety-related decision making and policies depends upon identifying, collecting, and interpreting safety-producing behaviors in addition to safety-reducing behaviors. Opportunities and challenges in collecting and analyzing the largely unexploited data on desired, safety-producing operator behaviors are discussed.
Focusing on undesired operator behaviors is pervasive in system design and safety management cultures in aviation. This focus limits the data that are collected, the questions that are asked during data analysis, and therefore our understanding of what operators do in everyday work. Human performance represents a significant source of aviation safety data that includes both desired and undesired actions. When safety is characterized only in terms of errors and failures, the vast majority of human impacts on system safety and performance are ignored. The outcomes of safety data analyses dictate what is learned from those data, which in turn informs safety policies and safety-related decision making. When learning opportunities are systematically restricted by focusing only on rare failure events, not only do we learn less (and less often), but we can draw misleading conclusions by relying on a non-representative sample of human performance data. Changes in how we define and think about safety can highlight new opportunities for collection and analysis of safety-relevant data. Developing an integrated safety picture to better inform safety-related decision making and policies depends upon identifying, collecting, and interpreting safety producing behaviors in addition to safety reducing behaviors. The panel will discuss opportunities and challenges in collecting and analyzing the largely unexploited data on desired, safety-producing operator behaviors.
Focusing on undesired operator behaviors is pervasive in system design and safety management cultures. This focus limits the data that are collected, the questions that are asked during data analysis, and therefore our understanding of what operators do in everyday work. Human performance represents a significant source of safety data that includes both desired and undesired actions. When safety is characterized only in terms of errors and failures, the vast majority of human impacts on system safety and performance are ignored. The outcomes of safety data analyses dictate what is learned from those data, which in turn informs safety policies and safety-related decision making. When learning opportunities are systematically restricted by focusing only on rare failure events, not only do we learn less (and less often), but we can draw misleading conclusions by relying on a non-representative sample of human performance data. The study of human contributions to safety represents a vast and largely unexplored opportunity to learn. Changes in how we define and think about safety can highlight new opportunities for collection and analysis of safety-relevant data. Developing an integrated safety picture to better inform system design, safety-related decision making and policies depends upon identifying, collecting, and interpreting safety producing behaviors in addition to safety reducing behaviors.
Recently, statistical distributions have been explored to provide estimates of the mineralogical diversity of Earth, and Earth-like planets. In this paper, a Bayesian approach is introduced to estimate Earth’s undiscovered mineralogical diversity. Samples are generated from a posterior distribution of the model parameters using Markov chain Monte Carlo simulations such that estimates and inference are directly obtained. It was previously shown that the mineral species frequency distribution conforms to a generalized inverse Gauss–Poisson (GIGP) large number of rare events model. Even though the model fit was good, the population size estimate obtained by using this model was found to be unreasonably low by mineralogists. In this paper, several zero-truncated, mixed Poisson distributions are fitted and compared, where the Poisson-lognormal distribution is found to provide the best fit. Subsequently, the population size estimates obtained by Bayesian methods are compared to the empirical Bayes estimates. Species accumulation curves are constructed and employed to estimate the population size as a function of sampling size. Finally, the relative abundances, and hence the occurrence probabilities of species in a random sample, are calculated numerically for all mineral species in Earth’s crust using the Poisson-lognormal distribution. These calculations are connected and compared to the calculations obtained in a previous paper using the GIGP model for which mineralogical criteria of an Earth-like planet were given.
NASA’s OSIRIS-REx mission re-turned material from asteroid Bennu on September 24, 2023, marking the first time a U.S. mission has delivered asteroid samples to Earth, and the largest asteroid sample return to date. Due to the pristine nature of these primitive carbonaceous-rich samples, they allow us a rare opportunity to study our solar system’s formation to a degree not previously possible. Isotopes of moderately volatile elements (MVEs) have been recently developed as robust tracers for tracking different volatilization events within our Solar System. Of the MVEs, K has gained significant interest in recent years due to its ideal chemical and physical properties combined with technique improvements. Due to this, several recent studies have investigated the K isotope systematics within bulk chondrites and found an isotopic dichotomy be-tween the carbonaceous and non-carbonaceous chondrites (Figure 1), likely reflecting their different reservoirs which formed in the inner and outer protoplanetary disk respectively. Furthermore, systematic K isotope variations across the different carbonaceous chondrite groups and correlations with mass independent isotope systems such as Cr, Ti, and Ni, have also been observed. As a result, establishing the K isotope composition of bulk Bennu can be used to test the mission hypothesis that “Bennu’s parent asteroid accreted in the outer protoplanetary disk, beyond Jupiter, as recorded by distinct isotopic anomalies in a variety of elements” . In addition to early solar system processes, K isotopes can also be fractionated by space weathering as shown by comparisons between mature and immature lunar regolith. The degree of K isotope fractionation caused by space weathering correlates with the regolith maturity index and is an order of magnitude larger than what is observed in bulk meteorite samples which have not undergone strong space weathering processes. As such, the K isotope systematics of Bennu samples could provide an independent assessment of regolith maturity of the asteroid surface, helping to directly test the mission hypothesis that “Space weathering changed the chemistry and mineralogy of optically active surfaces” . In order to test both this hypothesis, and the hypothesis relating to Bennu’s accretion location, we aim to conduct high-precision K isotope analysis on bulk Bennu aggregates.
Cosmic-ray exposure ages of lunar samples have been used to date surface features related to impact cratering and downslope movement of material. Only when multiple samples related to a feature have the same rare-gas exposure age or when a single sample has the same Kr-81 -Kr and track-exposure age can a feature be considered as reliably dated. Based on these criteria, there are only five well-dated lunar features: Cone Crater (Apollo 14), 26 m.y,; North Ray Crater (Apollo 16), 50 m.y.; South Ray Crater (Apollo 16), 2 m.y.; the emplacement of the Station 6 boulders (Apollo 17), 22 m.y.; and the emplacement of the Station 7 boulder (Apollo 17), 28 m.y. Other features are tentatively dated or have limits set on their ages: Bench Crater (Apollo 12), upper limit of 99 m.y.; Baby Ray Crater (Apollo 16), upper limit of 2 m.y.; Shorty Crater (Apollo 17), approximately 30 m.y.; Camelot Crater (Apollo 17) upper limit of 140 m.y.; the emplacement of the Station 2 boulder 1 (Apollo 17), 45 to 55 m.y.; and the slide which generated the light mantle (Apollo 17), lower limit of 50 m.y.
A method has been designed for using multiple independent stations to discriminate fast transient radio sources from local anomalies, such as antenna noise or radio frequency interference (RFI). This can improve the sensitivity of incoherent detection for geographically separated stations such as the very long baseline array (VLBA), the future square kilometer array (SKA), or any other coincident observations by multiple separated receivers. The transients are short, broadband pulses of radio energy, often just a few milliseconds long, emitted by a variety of exotic astronomical phenomena. They generally represent rare, high-energy events making them of great scientific value. For RFI-robust adaptive detection of transients, using multiple stations, a family of algorithms has been developed. The technique exploits the fact that the separated stations constitute statistically independent samples of the target. This can be used to adaptively ignore RFI events for superior sensitivity. If the antenna signals are independent and identically distributed (IID), then RFI events are simply outlier data points that can be removed through robust estimation such as a trimmed or Winsorized estimator. The alternative "trimmed" estimator is considered, which excises the strongest n signals from the list of short-beamed intensities. Because local RFI is independent at each antenna, this interference is unlikely to occur at many antennas on the same step. Trimming the strongest signals provides robustness to RFI that can theoretically outperform even the detection performance of the same number of antennas at a single site. This algorithm requires sorting the signals at each time step and dispersion measure, an operation that is computationally tractable for existing array sizes. An alternative uses the various stations to form an ensemble estimate of the conditional density function (CDF) evaluated at each time step. Both methods outperform standard detection strategies on a test sequence of VLBA data, and both are efficient enough for deployment in real-time, online transient detection applications.
Lunar meteorites are crucial to understand the Moon s geological history because, being samples of the lunar crust that have been ejected by random impact events, they potentially originate from areas outside the small regions of the lunar surface sampled by the Apollo and Luna missions. The Apollo and Luna sample sites are contained within the Procellarum KREEP Terrain (PKT, Jolliff et al., 2000), where KREEP refers to potassium, rare earth element, and phosphorus-rich lithologies. The KREEP-rich rocks in the PKT are thought to be derived from late-stage residual liquids after approx.95-99% crystallization of a lunar magma ocean (LMO). These are understood to represent late-stage liquids which were enriched in incompatible trace elements (ITE) relative to older rocks (Snyder et al., 1992). As a consequence, the PKT is a significant reservoir for Th and KREEP. However, the majority of the lunar surface is likely to be significantly more depleted in ITE (84%, Jolliff et al., 2000). Lunar meteorites that are low in KREEP and Th may thus sample regions distinct from the PKT and are therefore a valuable source of information regarding the composition of KREEP-poor lunar crust. Northwest Africa (NWA) 3163 is a thermally metamorphosed ferroan, feldspathic, granulitic breccia composed of igneous clasts with a bulk anorthositic, noritic bulk composition. It is relatively mafic (approx.5.8 wt.% FeO; approx.5 wt.% MgO) and has some of the lowest concentrations of ITEs (17ppm Ba) compared to the feldspathic lunar meteorite (FLM) and Apollo sample suites (Hudgins et al., 2011). Localized plagioclase melting and incipient melting of mafic minerals require localized peak shock pressures in excess of 45 GPa (Chen and El Goresy, 2000; Hiesinger and Head, 2006). NWA 3163, and paired samples NWA 4481 and 4883, have previously been interpreted to represent an annealed micro-breccia which was produced by burial metamorphism at depth in the ancient lunar crust (Fernandes et al., 2009). This is in contrast to the interpretation of Hudgins et al. (2009) where NWA 3163 was interpreted to have formed through contact metamorphism. To further constrain its origin, we examine the petrogenesis of NWA 3163 with a particular emphasis on in-situ measurement of trace elements within constituent minerals, Sm-Nd and Rb-Sr isotopic systematics on separated mineral fractions and petrogenetic modeling.