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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Two transitions in complex eigenvalue statistics: Hermiticity and integrability breaking

Open quantum systems have complex energy eigenvalues which are expected to follow non-Hermitian random matrix statistics, when chaotic, or two-dimensional (2d) Poisson statistics, when integrable. We investigate the spectral properties of a many-body quantum spin chain, i.e., the Hermitian Heisenberg model with imaginary disorder. Its rich complex eigenvalue statistics is found to separately break both Hermiticity and integrability at different scales of the disorder strength. With no disorder, the system is integrable and Hermitian, with spectral statistics corresponding to the 1d Poisson point process. At very small disorder, we find a transition from 1d Poisson statistics to an effective D -dimensional Poisson point process, showing Hermiticity breaking. At intermediate disorder, we find integrability breaking, as inferred from the statistics matching that of non-Hermitian complex symmetric random matrices in class AI † . For large disorder, as the spins align, we recover the expected integrability (now in the non-Hermitian setup), indicated by 2d Poisson statistics. These conclusions are based on fitting the spin-chain data of numerically generated nearest- and next-to-nearest-neighbor spacing distributions to an effective 2d Coulomb gas description at inverse temperature β . We confirm that such an effective description of random matrices also applies in classes AI † and AII † up to next-to-nearest-neighbor spacings. Published by the American Physical Society 2025

Akemann, Gernot (ORCID:0000000217104258)↗
DOE OSTI2023

Developing and applying quantifiable metrics for diagnostic and experiment design on Z

This project applies methods in Bayesian inference and modern statistical methods to quantify the value of new experimental data, in the form of new or modified diagnostic configurations and/or experiment designs. We demonstrate experiment design methods that can be used to identify the highest priority diagnostic improvements or experimental data to obtain in order to reduce uncertainties on critical inferred experimental quantities and select the best course of action to distinguish between competing physical models. Bayesian statistics and information theory provide the foundation for developing the necessary metrics, using two high impact experimental platforms on Z as exemplars to develop and illustrate the technique. We emphasize that the general methodology is extensible to new diagnostics (provided synthetic models are available), as well as additional platforms. We also discuss initial scoping of additional applications that began development in the last year of this LDRD.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Studies of the Ability to Hold the Eye in Eccentric Gaze: Measurements in Normal Subjects with the Head Erect

We studied the ability to hold the eyes in eccentric horizontal or vertical gaze angles in 68 normal humans, age range 19-56. Subjects attempted to sustain visual fixation of a briefly flashed target located 30 in the horizontal plane and 15 in the vertical plane in a dark environment. Conventionally, the ability to hold eccentric gaze is estimated by fitting centripetal eye drifts by exponential curves and calculating the time constant (t(sub c)) of these slow phases of gazeevoked nystagmus. Although the distribution of time-constant measurements (t(sub c)) in our normal subjects was extremely skewed due to occasional test runs that exhibited near-perfect stability (large t(sub c) values), we found that log10(tc) was approximately normally distributed within classes of target direction. Therefore, statistical estimation and inference on the effect of target direction was performed on values of z identical with log10t(sub c). Subjects showed considerable variation in their eyedrift performance over repeated trials; nonetheless, statistically significant differences emerged: values of tc were significantly higher for gaze elicited to targets in the horizontal plane than for the vertical plane (P less than 10(exp -5), suggesting eccentric gazeholding is more stable in the horizontal than in the vertical plane. Furthermore, centrifugal eye drifts were observed in 13.3, 16.0 and 55.6% of cases for horizontal, upgaze and downgaze tests, respectively. Fifth percentile values of the time constant were estimated to be 10.2 sec, 3.3 sec and 3.8 sec for horizontal, upward and downward gaze, respectively. The difference between horizontal and vertical gazeholding may be ascribed to separate components of the velocity position neural integrator for eye movements, and to differences in orbital mechanics. Our statistical method for representing the range of normal eccentric gaze stability can be readily applied in a clinical setting to patients who were exposed to environments that may have modified their central integrators and thus require monitoring. Patients with gaze-evoked nystagmus can be flagged by comparing to the above established normative criteria.

Reschke, Millard F.↗
NASA NTRS1998

On the Annual Frequency of Intense Hurricanes in Relation to the Extremes of ENSO and the Interludes Between Them

On the basis of Trenberth's quantitative definition for marking the occurrence of an El Nino, one can precisely identify some 15 El Nino and 10 La Nina events during the interval of 1950-1997. The statistical aspects of these identified extremes and the intervening periods between them (interludes) are determined. Also, a comparison of the appearances of these extremes and interludes with yearly hurricane seasons shows that of the last 48 hurricane seasons, 20 (42%) are El Nino-related (i.e., an El Nino was in progress during all, or part, of the yearly hurricane season - June-November), 13 (27%) are La Nina-related, and 15 (31%) are interlude - related. Combining the two subgroups of La Nino- and interlude - related seasons into a single grouping called non-El Nino-related seasons, one finds that the non-El Nino-related seasons have a mean annual frequency of intense hurricanes measuring 2.8, while the El Nino-related seasons have a mean annual frequency of intense hurricanes measuring 1.3, and the observed difference in the means is inferred to be statistically important at the 99.8% level of confidence. Therefore, during El Nino-related seasons, fewer intense hurricanes (typically, less than or equal to 2) should be expected, while durin(y non-El Nino-related seasons, more (typically, greater than or equal to 2) should be expected. Implications for the upcoming 1998 and future hurricane seasons are discussed.

Wilson, Robert M.↗
NASA NTRS1998

Statistical Aspects of ENSO Events (1950-1997) and the El Nino-Atlantic Intense Hurricane Activity Relationship

On the basis of Trenberth's quantitative definition for marking the occurrence of an El Nino (or La Nina), one can precisely identify by month and year the starts and ends of some 15 El Nino and 10 La Nina events during the interval of 1950-1997, an interval corresponding to the most reliable for cataloging intense hurricane activity in the Atlantic basin (i.e., those of category 3-5 on the Saffir-Simpson hurricane scale). The main purpose of this investigation is primarily two-fold: First, the statistical aspects of these identified extremes and the intervening periods between them (called "interludes") are examined and, second, the statistics of the seasonal frequency of intense hurricanes in comparison to the extremes and interludes are determined. This study clearly demonstrates that of the last 48 hurricane seasons, 20 (42 percent) can be described as being "El Nino-related" (i.e., an El Nino was in progress during all, or part, of the yearly hurricane season--June-November), 13 (27 percent) as "La Nina-related" (i.e., a La Nina was in progress during all, or part, of the yearly hurricane season), and 15 (31 percent) as "interlude-related" (i.e., neither an El Nino nor a La Nina was in progress during any portion of the yearly hurricane season). Combining the latter two subgroups into a single grouping called "non-El Nino-related" seasons, one finds that they have had a mean frequency of intense hurricanes measuring 2.8 events per season, while the El Nino-related seasons have had a mean frequency of intense hurricanes measuring 1.3 events per season, where the observed difference in the means is inferred to be statistically important at the 99.8-percent level of confidence. Therefore, as previously shown more than a decade ago using a different data set, there undeniably exists an El Nino-Atlantic hurricane activity relationship, one which also extends to the class of intense hurricanes. During the interval of 1950-1997, fewer intense hurricanes occurred during El Nino-related seasons (always less than or equal to 3 and usually less than or equal to 2, this latter value having been true for 18 of the 20 El Nino-related seasons), while more usually occurred during non-El Nino-related seasons (typically greater than or equal to 2, having been true for 22 of the 28 non-El Nino-related seasons). Implications for the 1998 and 1999 hurricane seasons are discussed.

Wilson, Robert M.↗
DOE OSTI2023

Direct Estimation of Parameters in ODE Models Using WENDy: Weak-Form Estimation of Nonlinear Dynamics

Abstract We introduce the Weak-form Estimation of Nonlinear Dynamics (WENDy) method for estimating model parameters for non-linear systems of ODEs. Without relying on any numerical differential equation solvers, WENDy computes accurate estimates and is robust to large (biologically relevant) levels of measurement noise. For low dimensional systems with modest amounts of data, WENDy is competitive with conventional forward solver-based nonlinear least squares methods in terms of speed and accuracy. For both higher dimensional systems and stiff systems, WENDy is typically both faster (often by orders of magnitude) and more accurate than forward solver-based approaches. The core mathematical idea involves an efficient conversion of the strong form representation of a model to its weak form, and then solving a regression problem to perform parameter inference. The core statistical idea rests on the Errors-In-Variables framework, which necessitates the use of the iteratively reweighted least squares algorithm. Further improvements are obtained by using orthonormal test functions, created from a set of $$C^{\infty }$$ C ∞ bump functions of varying support sizes.We demonstrate the high robustness and computational efficiency by applying WENDy to estimate parameters in some common models from population biology, neuroscience, and biochemistry, including logistic growth, Lotka-Volterra, FitzHugh-Nagumo, Hindmarsh-Rose, and a Protein Transduction Benchmark model. Software and code for reproducing the examples is available at https://github.com/MathBioCU/WENDy .

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Modification of Eccentric Gaze-Holding

Clear vision and accurate localization of objects in the environment are prerequisites for reliable performance of motor tasks. Space flight confronts the crewmember with a stimulus rearrangement that requires adaptation to function effectively with the new requirements of altered spatial orientation and motor coordination. Adaptation and motor learning driven by the effects of cerebellar disorders may share some of the same demands that face our astronauts. One measure of spatial localization shared by the astronauts and those suffering from cerebellar disorders that is easily quantified, and for which a neurobiological substrate has been identified, is the control of the angle of gaze (the "line of sight"). The disturbances of gaze control that have been documented to occur in astronauts and cosmonauts, both in-flight and postflight, can be directly related to changes in the extrinsic gravitational environment and intrinsic proprioceptive mechanisms thus, lending themselves to description by simple non-linear statistical models. Because of the necessity of developing robust normal response populations and normative populations against which abnormal responses can be evaluated, the basic models can be formulated using normal, non-astronaut test subjects and subsequently extended using centrifugation techniques to alter the gravitational and proprioceptive environment of these subjects. Further tests and extensions of the models can be made by studying abnormalities of gaze control in patients with cerebellar disease. A series of investigations were conducted in which a total of 62 subjects were tested to: (1) Define eccentric gaze-holding parameters in a normative population, and (2) explore the effects of linear acceleration on gaze-holding parameters. For these studies gaze-holding was evaluated with the subjects seated upright (the normative values), rolled 45 degrees to both the left and right, or pitched back 30 and 90 degrees. In a separate study the further effects of acceleration on gaze stability was examined during centrifugation (+2 G (sub x) and +2 G (sub z) using a total of 23 subjects. In all of our investigations eccentric gaze-holding was established by having the subjects acquire an eccentric target (+/-30 degrees horizontal, +/- 15 degrees vertical) that was flashed for 750 msec in an otherwise dark room. Subjects were instructed to hold gaze on the remembered position of the flashed target for 20 sec. Immediately following the 20 sec period, subjects were cued to return to the remembered center position and to hold gaze there for an additional 20 sec. Following this 20 sec period the center target was briefly flashed and the subject made any corrective eye movement back to the true center position. Conventionally, the ability to hold eccentric gaze is estimated by fitting the natural log of centripetal eye drifts by linear regression and calculating the time constant (G) of these slow phases of "gaze-evoked nystagmus". However, because our normative subjects sometimes showed essentially no drift (tau (sub c) = m), statistical estimation and inference on the effect of target direction was performed on values of the decay constant theta = 1/(tau (sub c)) which we found was well modeled by a gamma distribution. Subjects showed substantial variance of their eye drifts, which were centrifugal in approximately 20 % of cases, and > 40% for down gaze. Using the ensuing estimated gamma distributions, we were able to conclude that rightward and leftward gaze holding were not significantly different, but that upward gaze holding was significantly worse than downward (p<0.05). We also concluded that vertical gaze holding was significantly worse than horizontal (p<0.05). In the case of left and right roll, we found that both had a similar improvement to horizontal gaze holding (p<0.05), but didn't have a significant effect on vertical gaze holding. For pitch tilts, both tilt angles significantly decreased gaze-holding ility in all directions (p<0.05). Finally, we found that hyper-g centrifugation significantly decreased gaze holding ability in the vertical plane. The main findings of this study are as follows: (1) vertical gaze-holding is less stable than horizontal, (2) gaze-holding to upward targets is less stable than to downward targets, (3) tilt affects gaze holding, and (4) hyper-g affects gaze holding. This difference between horizontal and vertical gaze-holding may be ascribed to separate components of the velocity-to-position neural integrator for eye movements, and to differences in orbital mechanics. The differences between upward and downward gaze-holding may be ascribed to an inherent vertical imbalance in the vestibular system. Because whole body tilt and hyper-g affects gaze-holding, it is implied that the otolith organs have direct connections to the neural integrator and further studies of astronaut gaze-holding are warranted. Our statistical method for representing the range of normal eccentric gaze stability can be readily applied to normals who maybe exposed to environments which may modify the central integrator and require monitoring, and to evaluate patients with gaze-evoked nystagmus by comparing to the above established normative criteria.

Reschke, M. F.↗
DOE OSTI2022

Computer Model Calibration with Time Series Data Using Deep Learning and Quantile Regression

Computer models play a key role in many scientific and engineering problems. One major source of uncertainty in computer model experiments is input parameter uncertainty. Computer model calibration is a formal statistical procedure to infer input parameters by combining information from model runs and observational data. The existing standard calibration framework suffers from inferential issues when the model output and observational data are high-dimensional dependent data, such as large time series, due to the difficulty in building an emulator and the nonidentifiability between effects from input parameters and data-model discrepancy. To overcome these challenges, we, in this work, propose a new calibration framework based on a deep neural network (DNN) with long short-term memory layers that directly emulates the inverse relationship between the model output and input parameters. Adopting the “learning with noise” idea, we train our DNN model to filter out the effects from data-model discrepancy on input parameter inference. We also formulate a new way to construct interval predictions for DNN using quantile regression to quantify the uncertainty in input parameter estimates. Through a simulation study and real data application with the Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro), we show our approach can yield accurate point estimates and well-calibrated interval estimates for input parameters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Mathematics: The Tao of Data Science

The two pieces, "Ten Research Challenge Areas in Data Science" by Jeannette M. Wing and “Challenges and Opportunities in Statistics and Data Science: Ten Research Areas” by Xuming He and Xihong Lin, provide an impressively complete list of data science challenges from luminaries in the field of data science. They have done an extraordinary job, so this response offers a complementary viewpoint from a mathematical perspective and evangelizes advanced mathematics as a key tool for meeting the challenges they have laid out. Notably, we pick up the themes of scientific understanding of machine learning and deep learning, computational considerations such as cloud computing and scalability, balancing computational and statistical considerations, and inference with limited data. We propose that mathematics is an important key to establishing rigor in the field of data science and as such has an essential role to play in its future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A Qualitative Strategy for Fusion of Physics into Empirical Models for Process Anomaly Detection

To facilitate the automated online monitoring of power plants, a systematic and qualitative strategy for anomaly detection is presented. This strategy is essential to provide credible reasoning on why and when an empirical versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. Empirical methods are usually based on pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The presented strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability, and suitability for training and testing, cause-effect, entropy inference, and model fitting. The strategy is demonstrated through a pilot use case for the application of anomaly detection to capture a valve packing leak at the high-pressure coolant injection system of a nuclear power plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

PROVABGS: The Probabilistic Stellar Mass Function of the BGS One-percent Survey

We present the probabilistic stellar mass function (pSMF) of galaxies in the DESI Bright Galaxy Survey (BGS), observed during the One-percent Survey. The One-percent Survey was one of DESI's survey validation programs conducted from 2021 April to May, before the start of the main survey. It used the same target selection and similar observing strategy as the main survey and successfully observed the spectra and redshifts of 143,017 galaxies in the r < 19.5 magnitude-limited BGS Bright sample and 95,499 galaxies in the fainter surface-brightness- and color-selected BGS Faint sample over z < 0.6. We derive pSMFs from posteriors of stellar mass, M*, inferred from DESI photometry and spectroscopy using the Hahn et al. PRObabilistic Value-Added BGS (PROVABGS) Bayesian spectral energy distribution modeling framework. We use a hierarchical population inference framework that statistically and rigorously propagates the M* uncertainties. Furthermore, we include correction weights that account for the selection effects and incompleteness of the BGS observations. We present the redshift evolution of the pSMF in BGS, as well as the pSMFs of star-forming and quiescent galaxies classified using average specific star formation rates from PROVABGS. Overall, the pSMFs show good agreement with previous stellar mass function measurements in the literature. Our pSMFs showcase the potential and statistical power of BGS, which in its main survey will observe >100 × more galaxies. Moreover, we present the statistical framework for subsequent population statistics measurements using BGS, which will characterize the global galaxy population and scaling relations at low redshifts with unprecedented precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Constraining the Twomey effect from satellite observations: issues and perspectives

Abstract. The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd, ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd, ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, ΔNd, ant, remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of metres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining ΔNd, ant, namely the quantification of (i) the cloud-active aerosol – the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) Nd, (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd-to-CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Martian cratering revisited - Implications for early geologic evolution

Consideration is given to the geological history of Mars as inferred from cratering statistics. The geomorphology of the cratered terrain in Terra Tyrrhena is described in detail, and crater counts made from Viking images of cratered terrain as well as pure cratered areas from the Southern Hemisphere, craters superposing both the intercrater plains and dissected terrain, and plains units in the Northern Hemisphere are presented. Comparison of the Martian crater counts with those obtained for the lunar highlands reveals the distribution functions to be quite similar for crater diameters greater than 8 km, indicating their derivation from the same population of bodies, with an integrated Mars/moon crater flux ratio of at least 0.75. Monte Carlo simulations reveal that if this ratio was due to resurfacing processes, then the Martian population is probably a remnant of obliteration by both inter- and intra-crater plains acting in concert. Results also suggest that most of the endogenetic activity in the cratered terrain occured before the end of heavy bombardment and that two stages of geologic activity were present.

Gurnis, M.↗
NASA NTRS1989

A heat-pipe mechanism for volcanism and tectonics on Venus

A heat-pipe mechanism is proposed for the transport of heat through the lithosphere of Venus. This mechanism allows the crust and lithosphere on Venus to be greater than 150 km. thick. A thick basaltic crust on Venus is expected to transform eclogite at a depth of 60 to 80 km; the dense eclogite would contribute to lithospheric delamination that returns the crust to the interior of the planet completing the heat-pipe cycle. Topography and the associated gravity anomalies can be explained by Airy compensation of the thick crust. The principal observation that is contrary to this hypothesis is the mean age of the surface that is inferred from crater statistics; the minimum mean age is about 130 Myr and this implies an upper limit of 2 cubic kilometers per year for the surface volcanic flux. If the heat-pipe mechanism was applicable on the Earth in the Archean it would provide the thick lithosphere implied by isotopic data from diamonds.

Turcotte, D. L.↗
NASA NTRS1989

A heat-pipe mechanism for volcanism and tectonics on Venus

A heat-pipe mechanism is proposed for the transport of heat through the lithosphere of Venus. This mechanism allows the crust and lithosphere on Venus to be greater than 150 km thick. A thick basaltic crust on Venus is expected to transform eclogite at a depth of 60 to 80 km; the dense eclogite would contribute to lithospheric delamination that returns the crust to the interior of the planet completing the heat-pipe cycle. Topography and the associated gravity anomalies can be explained by Airy compensation of the thick crust. The principal observation that is contrary to this hypothesis is the mean age of the surface that is inferred from crater statistics; the minimum mean age is about 130 Myr and this implies an upper limit of 2 cubic kilometers per year for the surface volcanic flux. If the heat-pipe mechanism was applicable on the earth in the Archean it would provide the thick lithosphere implied by isotopic data from diamonds.

Turcotte, D. L.↗
NASA NTRS1999

Surface Ages and Resurfacing Rates of the Polar Layered Deposits on Mars

The martian polar layered deposits (PLD) are probably the best source of information about the recent climate history of Mars, but their origin and the mechanisms of accumulation are still a mystery. The polar layers are sedimentary deposits that most planetary scientists believe are composed of water ice and varying amounts of wind-blown dust, but their composition is poorly constrained. Interpretation of the observed polar stratigraphy in terms of global climate changes is complicated by the significant difference in surface ages between the north and south PLD inferred from crater statistics. While no craters have been found in the north PLD, the surface of the south PLD appears to have been stable for many of the orbital/axial cycles that are thought to have induced global climate changes on Mars. Using medium-resolution Viking imagery, Plaut et al. found at least 15 impact craters in the southern layered deposits and concluded that their surface is 120 +/- 40 million years old. In contrast, Cutts et al. found no fresh impact craters larger than about 300 meters in summertime images of the north polar layered deposits. Additional information is contained in the original extended abstract.

Herkenhoff, K. E.↗