California Institute of Technology
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Recent publications
Identifying modal parameters from vibration measurements is an essential step for modal analysis and modeling of structural dynamics. A critical challenge in modal parameter identification is the determination of the physical modes from spurious modes, especially with noisy measurement data. In this study, an approach is presented to enable automated identification of modal parameters by quantifying the spatial features of full-field, high-spatial-resolution response measurements. Specifically, it is derived that the local variances of the physical and spurious mode shapes are drastically distinguishing, especially when the spatial resolution of the response measurement is high (i.e., full-field with dense spatial measurement points). This allows an effective identification of the physical modes from spurious. Experimental studies are conducted on a few structural models and detailed comparisons are performed and discussed between the presented method and existing methods, including parametric and non-parametric.
A large body of research illustrates the prioritization of goal-relevant information in memory; however, it is unclear how reward-related memories are organized. Using a rewarded free recall paradigm, we investigated how reward motivation structures the organization of memory around temporal and higher-order contexts. To better understand these processes, we simulated our findings using a reward-modulated variant of the Context Maintenance and Retrieval Model (CMR; Polyn et al., 2009). In the first study, we found that reward did not influence temporal clustering, but instead shifted the organization of memory based on reward category. Further, we showed that a reward-modulated learning rate and source features of CMR most accurately depict reward's enhancement on memory and clustering by value. In a second study, we showed that reward-memory effects can exist in both extended periods of sustained motivation and frequent changes in motivation, by showing equivalent reward effects using mixed- and pure-list motivation manipulations. However, we showed that a reward-modulated learning rate in isolation can support reward's enhancement of memory in pure-list contexts. Overall, we conclude that reward-related memories are adaptively organized by higher-order value information, and contextual binding to value contexts may only be necessary when rewards are intermittent versus sustained.
Objective Real time, high fidelity estimation and reconstruction of brain wave dynamics is complicated by the nonstationary and nonlinear effects of electroencephalography (EEG) measures. This work aims to introduce a novel state space architecture, which continuously updates a linear brain wave model and estimates the exogenous input to the brain wave system. This continuous update is adaptive, because the estimator continuously monitors its own performance and can modify its own parameters by a closed loop action. This highly nonlinear estimator should reconstruct the EEG measure in real time for analysis and diagnostic information. Methods The development of this adaptive unknown input estimator focuses on treating the known phenomena of brain waves. The adaptive law accounts for nonlinearities in the EEG measure while the input estimator simultaneously accounts for the exogenous input to the system. The estimator is further robust to general process uncertainty in the plant dynamics. Results The stability of the adaptive unknown input estimator for EEG measures is shown. This estimator is shown to outperform standard linear models, such as Kalman filtering techniques especially at points where the EEG measure changes sharply. Conclusion This adaptive unknown input estimator reconstructs unmodeled EEG data in real time by accounting for the nonlinear brain wave dynamics. Because the adaptive law updates a linear model over time, much of the interpretability and intuition of linear state space modeling is preserved.
The Ramsey number r(H) of a graph H is the minimum integer n such that any two-coloring of the edges of the complete graph Kn contains a monochromatic copy of H. While this definition only asks for a single monochromatic copy of H, it is often the case that every two-edge-coloring of the complete graph on r(H) vertices contains many monochromatic copies of H. The minimum number of such copies over all two-colorings of Kr(H) will be referred to as the threshold Ramsey multiplicity of H. Addressing a problem of Harary and Prins, who were the first to systematically study this quantity, we show that there is a positive constant c such that the threshold Ramsey multiplicity of a path or an even cycle on k vertices is at least (ck)k. This bound is tight up to the constant c. We prove a similar result for odd cycles in a companion paper.
We extend the model-free Data-Driven computing paradigm to solids and structures that are stochastic due to intrinsic randomness in the material behavior. The behavior of such materials is characterized by a likelihood measure instead of a constitutive relation. We specifically assume that the material likelihood measure is known only through an empirical point-data set in material or phase space. The state of the solid or structure is additionally subject to compatibility and equilibrium constraints. The problem is then to infer the likelihood of a given structural outcome of interest. In this work, we present a Data-Driven method of inference that determines likelihoods of outcomes from the empirical material data and that requires no material or prior modeling. In particular, the computation of expectations is reduced to explicit sums over local material data sets and to quadratures over admissible states, i.e., states satisfying compatibility and equilibrium. The complexity of the material data-set sums is linear in the number of data points and in the number of members in the structure. Efficient population annealing procedures and fast search algorithms for accelerating the calculations are presented. The scope, cost and convergence properties of the method are assessed with the aid selected applications and benchmark tests.
The primary objective of this chapter is to present an overview of the different key technologies that will be needed in order to fly the technically most challenging of the representative missions identified in Chapter 4 (the Pillar 2 Horizon 2061 report, Lasue et al., 2021). It starts with a description of the future scientific instruments which will address the key questions of Horizon 2061 described in Chapter 3 (the Pillar 1 Horizon 2061 report, Dehant et al., 2021) and the new technologies that the next generations of space instruments will require (Section 2). From there, the chapter follows the line of logical development and implementation of a planetary mission: Section 3 describes some of the novel mission architectures that will be needed and how they will articulate interplanetary spacecraft and science platforms; Section 4 summarizes the system-level technologies needed: power, propulsion, navigation, communication, advanced autonomy on-board planetary spacecraft; Section 5 describes the diversity of specialized science platforms that will be needed to survive, operate, and return scientific data from the extreme environments that future missions will target; Section 6 describes the new technology developments that will be needed for long-duration missions and semipermanent settlements; finally, Section 7 attempts to anticipate some of the disruptive technologies that should emerge and progressively prevail in the decades to come to meet the long-term needs of future planetary missions.
This chapter reviews for each province and destination of the Solar System the representative space missions that will have to be designed and implemented by 2061 to address the six key science questions about the diversity, origins, workings, and habitability of planetary systems (described in Chapter 1) and to perform the critical observations that have been described in Chapter 3 and partly Chapter 2. It derives from this set of future representative missions, some of which will have to be flown during the 2041–61 period, the critical technologies and supporting infrastructures that will be needed to fly these challenging missions, thus laying the foundation for the description of technologies and infrastructures for the future of planetary exploration that is given in Chapters 5 and 6Chapter 5Chapter 6, respectively.
There exists considerable uncertainty about the most appropriate functional form to describe mortality at the highest trophic level (the closure problem). Although linear and quadratic formulations predict strongly different dynamics, it is unclear which of these formulations is more realistic. We introduce an implicit predator population feeding on the highest trophic level, parameterized through a Holling Type II functional response and empirically observed predator–prey scaling relations. Thus, we arrive at a hyperbolic mortality formulation that is a hybrid between the linear and quadratic forms. Subsequently, we investigate the impact of this formulation on the modeled population dynamics. In particular, we compare the stability properties of simple food-chain models with a hyperbolic mortality and a linear mortality. Contrary to classical theory, the model with a hyperbolic mortality does not exhibit destabilization due to nutrient enrichment. For this model, we find that limit cycles are rather associated with a top-heavy ecosystem structure (high predator, low prey densities). The weak response to enrichment emerges because populations of both the predator and prey increase with nutrient supply, consistent with observations. We discuss the mechanism behind the relationship between top-heaviness and instability from an ecological and a mathematical perspective.
Remote sensing enhances large-scale biodiversity monitoring by overcoming temporal and spatial limitations of ground-based measurements and allows assessment of multiple plant traits simultaneously. The total set of traits and their variation over time is specific for each individual and can reveal information about the genetic composition of forest communities. Measuring trait variation among individuals of one species continuously across space and time is a key component in monitoring genetic diversity but difficult to achieve with ground-based methods. Remote sensing approaches using imaging spectroscopy can provide high spectral, spatial, and temporal coverage to advance the monitoring of genetic diversity, if sufficient relation between spectral and genetic information can be established. We assessed reflectance spectra from individual Fagus sylvatica L. (European beech) trees acquired across eleven years from 69 flights of the Airborne Prism Experiment (APEX) above the same temperate forest in Switzerland. We derived reflectance spectra of 68 canopy trees and correlated differences in these spectra with genetic differences derived from microsatellite markers among the 68 individuals. We calculated these correlations for different points in time, wavelength regions and relative differences between wavelength regions. High correlations indicate high spectral-genetic similarities. We then tested the influence of environmental variables obtained at temporal scales from days to years on spectral-genetic similarities. We performed an uncertainty propagation of radiance measurements to provide a quality indicator for these correlations. We observed that genetically similar individuals had more similar reflectance spectra, but this varied between wavelength regions and across environmental variables. The short-wave infrared regions of the spectrum, influenced by water absorption, seemed to provide information on the population genetic structure at high temperatures, whereas the visible part of the spectrum, and the near-infrared region affected by scattering properties of tree canopies, showed more consistent patterns with genetic structure across longer time scales. Correlations of genetic similarity with reflectance spectra similarity were easier to detect when investigating relative differences between spectral bands (maximum correlation: 0.40) than reflectance data (maximum correlation: 0.33). Incorporating uncertainties of spectral measurements yielded improvements of spectral-genetic similarities of 36% and 20% for analyses based on single spectral bands, and relative differences between spectral bands, respectively. This study highlights the potential of dense multi-temporal airborne imaging spectroscopy data to detect the genetic structure of forest communities. We suggest that the observed temporal trajectories of reflectance spectra indicate physiological and possibly genetic constraints on plant responses to environmental change.
Waterways’ regeneration is proposed as one of the main mitigation strategies for addressing the alarming water budget deficit in the populous, hyper-arid Egypt, relying primarily on the Nile as its most important water source. The latter is increasingly under pressure from a rise in internal consumption, droughts, and upstream damming. We perform herein a review of the state of knowledge of waterways in the Nile Delta and the environmental drivers that resulted in their degradation. We suggest a landscape-based design built on the Nile’s natural heritage to efficiently regenerate the areas surrounding these waterways to enable their role in addressing the water budget deficit and ensuring sustainable ecosystem services.
In this paper we present the results from an empirical power comparison of 40 goodness-of-fit tests for the univariate Laplace distribution, carried out using Monte Carlo simulations with sample sizes n=20,50,100,200, significance levels α=0.01,0.05,0.10, and 400 alternatives consisting of asymmetric and symmetric light/heavy-tailed distributions taken as special cases from 11 models. In addition to the unmatched scope of our study, an interesting contribution is the proposal of an innovative design for the selection of alternatives. The 400 alternatives consist of 20 specific cases of 20 submodels drawn from the main 11 models. For each submodel, the 20 specific cases corresponded to parameter values chosen to cover the full power range. An analysis of the results leads to a recommendation of the best tests for five different groupings of the alternative distributions. A real-data example is also presented, where an appropriate test for the goodness-of-fit of the univariate Laplace distribution is applied to weekly log-returns of Amazon stock over a recent four-year period.
In this short note, we prove an asymptotic expansion for the ratio of the Dirichlet density to the multivariate normal density with the same mean and covariance matrix. The expansion is then used to derive an upper bound on the total variation between the corresponding probability measures and rederive the asymptotic variance of the Dirichlet kernel estimators introduced by Aitchison & Lauder (1985) and studied theoretically in Ouimet (2020). Another potential application related to the asymptotic equivalence between the Gaussian variance regression problem and the Gaussian white noise problem is briefly mentioned but left open for future research.
From low temperatures through the Curie temperatures, the phonon density of states (DOS) was measured for bcc ⁵⁷Fe, and the partial phonon DOS was measured for cementite, ⁵⁷Fe3C, by nuclear resonant inelastic x-ray scattering (NRIXS). Nuclear forward scattering (NFS) was used to determine the state of magnetization of ⁵⁷Fe3C. The changes in phonon DOS with magnetization were assessed, and a linear relationship was found between the temperature dependences of the magnetization and the non-quasiharmonic shifts of phonon frequencies. Following the quasiharmonic approximation (QHA) for non-harmonic phonons, a magnetic quasiharmonic theory is developed to account for how phonon frequencies are altered by changes in magnetization. The formalism explains well the discrepancy between the free energy measurements and predictions of the QHA for both bcc iron and cementite. The physical origin of the magnetic Grüneisen parameters remains a challenge.
The goal of classifying shock metamorphic features in meteorites is to estimate the corresponding shock pressure conditions. However, the temperature variability of shock metamorphism is equally important and can result in a diverse and heterogeneous set of shock features in samples with a common overall shock pressure. In particular, high-pressure (HP) minerals, which were previously used as a solid indicator of high shock pressure in meteorites, require complex pressure–temperature–time ( P–T–t ) histories to form and survive. First, parts of the sample must be heated to melting temperatures, at high pressure, to enable rapid formation of HP minerals before pressure release. Second, the HP minerals must be rapidly cooled to below a critical temperature, before the pressure returns to ambient conditions, to avoid retrograde transformation to their low-pressure polymorphs. These two constraints require the sample to contain large temperature heterogeneities, e.g. melt veins in a cooler groundmass, during shock. In this study, we calculated shock temperatures and possible P–T paths of chondritic and differentiated mafic–ultramafic rocks for various shock pressures. These P–T conditions and paths, combined with observations from shocked meteorites, are used to constrain shock conditions and P–T – t histories of HP-mineral bearing samples. The need for rapid thermal quench of HP phases requires a relatively low bulk-shock temperature and therefore moderate shock pressures below ~ 30 GPa, which matches the stabilities of these HP minerals. The low-temperature moderate-pressure host rock generally shows moderate shock-deformation features consistent with S4 and, less commonly, S5 shock stages. Shock pressures in excess of 50 GPa in meteorites result in melt breccias with high overall post-shock temperatures that anneal out HP-mineral signatures. The presence of ringwoodite, which is commonly considered an indicator of the S6 shock stage, is inconsistent with pressures in excess of 30 GPa and does not represent shock conditions different from S4 shock conditions. Indeed, ringwoodite and coexisting HP minerals should be considered as robust evidence for moderate shock pressures (S4) rather than extreme shock (S6) near whole-rock melting.
Charge transport in organic molecular crystals (OMCs) is conventionally categorized into two limiting regimes − band transport, characterized by weak electron-phonon (e-ph) interactions, and charge hopping due to localized polarons formed by strong e-ph interactions. However, between these two limiting cases there is a less well understood intermediate regime where polarons are present but transport does not occur via hopping. Here we show a many-body first-principles approach that can accurately predict the carrier mobility in this intermediate regime and shed light on its microscopic origin. Our approach combines a finite-temperature cumulant method to describe strong e-ph interactions with Green-Kubo transport calculations. We apply this parameter-free framework to naphthalene crystal, demonstrating electron mobility predictions within a factor of 1.5−2 of experiment between 100 and 300 K. Our analysis reveals the formation of a broad polaron satellite peak in the electron spectral function and the failure of the Boltzmann equation in the intermediate regime.
Sixth-generation wireless networks will aggregate higher-than-ever mobile traffic into ultra-high capacity backhaul links, which could be deployed on the largely untapped spectrum above 100 GHz. Current regulations however prevent the allocation of large contiguous bands for communications at these frequencies, since several narrow bands are reserved to protect passive sensing services. These include radio astronomy and Earth exploration satellites using sensors that suffer from harmful interference from active transmitters. Here we show that active and passive spectrum sharing above 100 GHz is feasible by introducing and experimentally evaluating a real-time, dual-band backhaul prototype that tracks the presence of passive users (in this case the NASA satellite Aura) and avoids interference by automatically switching bands (123.5–140 GHz and 210–225 GHz). Our system enables wide-band transmissions in the above-100-GHz spectrum, while avoiding harmful interference to satellite systems, paving the way for innovative spectrum policy and technologies in these crucial bands.
We examine the prospects of utilizing matter-wave Fabry–Pérot interferometers for enhanced inertial sensing applications. Our study explores such tunneling-based sensors for the measurement of accelerations in two configurations: (a) a transmission setup, where the initial wave packet is transmitted through the cavity and (b) an out-tunneling scheme with intra-cavity generated initial states lacking a classical counterpart. We perform numerical simulations of the complete dynamics of the quantum wave packet, investigate the tunneling through a matter-wave cavity formed by realistic optical potentials and determine the impact of interactions between atoms. As a consequence we estimate the prospective sensitivities to inertial forces for both proposed configurations and show their feasibility for serving as inertial sensors.
The development of functionally graded materials via powder-based directed energy deposition is of interest to fabricate metallic aerospace components with tailored spatial properties. Currently, multi-metal and functionally graded metallic samples are fabricated with the transition or gradient in the build direction due to equipment hardware and software limitations. To enable full spatial control of component composition and properties, the development of a process for creating in-plane gradients and an understanding of the influence of process parameters on interfacial properties is necessary. This work highlights the manufacturing of in-plane gradients through powder-based directed energy deposition for SS316 and M300 maraging steel. An exploration of the influence of process parameters is performed, including the correlation of material deposition spacing, interfacial gradient strategy, and re-melting blank laser scans, with sample hardness, composition, and interface morphology. Finally, the in-plane gradient strategy is utilized to create a prototype geometry with a low- coefficient of thermal expansion.
Transfer functions are constantly used in both Seismology and Geotechnical Earthquake Engineering to relate seismic ground motion at different depths within strata. In the context of diffusive theory, they also appear in the expression of the imaginary part of 1D Green’s functions. In spite of their remarkable importance, their mathematical structure is not fully understood yet, except in the simplest cases of two or three layers at most. This incomplete understanding, in particular as to the effect of increasing number of layers, hinders progress in some areas, as researchers have to resort to expensive and less conclusive numerical parametric studies. This text presents the general form of transfer functions for any number of layers, overcoming the above issues. The mathematical structure of these transfer functions comes defined as a superposition of independent harmonics, whose number, amplitudes and periods we fully characterize in terms of the properties of the layers in closed-form. Owing to the formal connection between seismic wave propagation and other phenomena that, in essence, represent different instances of wave propagation in a linear-elastic medium, we have extended the results derived elsewhere, in the context of longitudinal wave propagation in modular rods, to seismic response of stratified sites. The ability to express the reciprocal of transfer functions as a superposition of independent harmonics enables new analytical approaches to assess the effect of each layer over the overall response. The knowledge of the general closed-form expression of the transfer functions allows to analytically characterize the long-wavelength asymptotics of the horizontal-to-vertical spectral ratio for any number of layers.
High spatial resolution land surface temperature (LST, <100 m) is crucial for agricultural water management, crop water stress monitoring, fire mapping, urban heat island study and volcano eruption detection. LST retrievals from the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) launched in June 2018, together with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER, launched in 1999) and the Landsat series (since 1972), comprise the state-of-the-art high spatial resolution LST datasets publicly accessible. Recently, we generated the ECOSTRESS LST product over Europe and Africa using both the temperature and emissivity separation (TES) and split-window (SW) algorithms under the European ECOSTRESS Hub (EEH). Here, we validated the official Jet Propulsion Laboratory (JPL) TES (Collection 1), EEH TES and EEH SW ECOSTRESS LST products over Europe and Africa between August 1, 2018 and December 31, 2021 by comparing against the in-situ measurements at 9 sites over a wide variety of land cover types. Meanwhile, the validation results were compared with those obtained for ASTER and Landsat LST at the same sites for a thorough understanding of the consistency among these high spatial resolution LST products. The results reveal that the three ECOSTRESS LST products have consistent performances, with an overall RMSE around 2 K. A cold bias around 1 K exists for all three ECOSTRESS LST, which is presumably originated from the radiometric calibration of the sensor in Collection 1 data. The Landsat LST shows a similar accuracy, with an RMSE of 2.20 K and bias of 0.54 K. The EEHSW LST show the highest consistency with Landsat LST, possibly due to the identical emissivity correction process. The performance of ASTER LST is also similar, with an RMSE of 1.98 K and bias of 0.9 K. The precisions of all the LST products are around 1.5 K. Future recalibration of the ECOSTRESS Level 1 radiance data in Collection 2 is expected to further improve the accuracy of ECOSTRESS LST. Overall, this study supports the adaptation of LST retrieval algorithms for the future thermal missions.
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Chiara Mingarelli
  • Department of Astronomy
Christian Andrew Grove
  • Division of Biology
Kyongsik Yun
  • Jet Propulsion Laboratory, Computation and Neural Systems
Emre Havazli
  • Jet Propulsion Laboratory
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