Accelerating global parameter estimation of gravitational waves from Galactic binaries using a genetic algorithm and GPUs

The Laser Interferometer Space Antenna (LISA) is a planned space-based gravitational wave telescope with the goal of measuring gravitational waves in the milli-Hertz frequency band, which is dominated by millions of Galactic binaries. While some of these binaries produce signals that are loud enough to stand out and be extracted, most of them blur into a confusion foreground. Current methods for analyzing the full frequency band recorded by LISA to extract as many Galactic binaries as possible and to obtain Bayesian posterior distributions for each of the signals are computationally expensive. We introduce a new approach to accelerate the extraction of the best fitting solutions for Galactic binaries across the entire frequency band from data with multiple overlapping signals. Furthermore, we use these best fitting solutions to omit the burn-in stage of a Markov chain Monte Carlo method and to take full advantage of GPU-accelerated signal simulation, allowing us to compute posterior distributions in 2 seconds per signal on a laptop-grade GPU.Comment: 13 pages, 11 figure

Bayesian parameter-estimation of Galactic binaries in LISA data with Gaussian Process Regression

The Laser Interferometer Space Antenna (LISA), which is currently under construction, is designed to measure gravitational wave signals in the milli-Hertz frequency band. It is expected that tens of millions of Galactic binaries will be the dominant sources of observed gravitational waves. The Galactic binaries producing signals at mHz frequency range emit quasi monochromatic gravitational waves, which will be constantly measured by LISA. To resolve as many Galactic binaries as possible is a central challenge of the upcoming LISA data set analysis. Although it is estimated that tens of thousands of these overlapping gravitational wave signals are resolvable, and the rest blurs into a galactic foreground noise; extracting tens of thousands of signals using Bayesian approaches is still computationally expensive. We developed a new end-to-end pipeline using Gaussian Process Regression to model the log-likelihood function in order to rapidly compute Bayesian posterior distributions. Using the pipeline we are able to solve the Lisa Data Challange (LDC) 1-3 consisting of noisy data as well as additional challenges with overlapping signals and particularly faint signals.Comment: 12 pages, 10 figure

First Focal Mechanisms of Marsquakes

Since February 2019, NASA's InSight lander is recording seismic signals on the planet Mars, which, for the first time, allows to observe ongoing tectonic processes with geophysical methods. A number of Marsquakes have been located in the Cerberus Fossae graben system in Elysium Planitia and further west, in the Orcus Patera depression. We present a first study of the focal mechanisms of three well-recorded events (S0173a, S0183a, S0235b) to determine the processes dominating in the source region. We infer for all three events a predominantly extensional setting. Our method is adapted to the case of a single, multicomponent receiver and based on fitting waveforms of P and S waves against synthetic seismograms computed for the initial crustal velocity model derived by the InSight team. We explore the uncertainty due to the single-station limitation and find that even data recorded by one station constrains the mechanisms (reasonably) well. For the events in the Cerberus Fossae region (S0173a, S0235b) normal faulting with a relatively steep dipping fault plane is inferred, suggesting an extensional regime mainly oriented E-W to NE-SW. The fault regime in the Orcus Patera region is not determined uniquely because only the P wave can be used for the source inversion. However, we find that the P and weak S waves of the S0183a event show similar polarities to the event S0173, which indicates similar fault regimes

Geostatistical analysis of centimeter-scale hydraulic conductivity variations at the MADE site

This is the published version. Copyright American Geophysical Union[1] Spatial variations in hydraulic conductivity (K) provide critical controls on solute transport in the subsurface. Recently, new direct-push tools were developed for high-resolution characterization of K variations in unconsolidated settings. These tools were applied to obtain 58 profiles (vertical resolution of 1.5 cm) from the heavily studied macrodispersion experiment (MADE) site. We compare the data from these 58 profiles with those from the 67 flowmeter profiles that have served as the primary basis for characterizing the heterogeneous aquifer at the site. Overall, the patterns of variation displayed by the two data sets are quite similar, in terms of both large-scale structure and autocorrelation characteristics. The direct-push K values are, on average, roughly a factor of 5 lower than the flowmeter values. This discrepancy appears to be attributable, at least in part, to opposite biases between the two methods, with the current versions of the direct-push tools underestimating K in the highly permeable upper portions of the aquifer and the flowmeter overestimating K in the less permeable lower portions. The vertically averaged K values from a series of direct-push profiles in the vicinity of two pumping tests at the site are consistent with the K estimates from those tests, providing evidence that the direct-push estimates are of a reasonable magnitude. The results of this field demonstration show that direct-push profiling has the potential to characterize highly heterogeneous aquifers with a speed and resolution that has not previously been possible

Seismic detection of the martian core by InSight

A plethora of geophysical, geo- chemical, and geodynamical observations indicate that the terrestrial planets have differentiated into silicate crusts and mantles that surround a dense core. The latter consists primarily of Fe and some lighter alloying elements (e.g., S, Si, C, O, and H) [1]¿. The Martian meteorites show evidence of chalcophile element depletion, suggesting that the otherwise Fe-Ni- rich core likely contains a sulfide component, which influences physical state

Seismic detection of the martian core

Clues to a planet's geologic history are contained in its interior structure, particularly its core. We detected reflections of seismic waves from the core-mantle boundary of Mars using InSight seismic data and inverted these together with geodetic data to constrain the radius of the liquid metal core to 1830 +/- 40 kilometers. The large core implies a martian mantle mineralogically similar to the terrestrial upper mantle and transition zone but differing from Earth by not having a bridgmanite-dominated lower mantle. We inferred a mean core density of 5.7 to 6.3 grams per cubic centimeter, which requires a substantial complement of light elements dissolved in the iron-nickel core. The seismic core shadow as seen from InSight's location covers half the surface of Mars, including the majority of potentially active regions-e.g., Tharsis-possibly limiting the number of detectable marsquakes.This is InSight contribution 200. We acknowledge NASA, CNES, and partner agencies and institutions (UKSA, SSO, ESA-PRODEX, DLR, JPL, IPGP-CNRS, ETHZ, IC, and MPS-MPG) for the development of SEIS. Numerical simulations were supported by a grant from the Swiss National Supercomputing Centre (CSCS) under project ID s922 as well as HPC resources of CINES under the allocation A0090407341, made by GENCI. We thank B. Dintrans, director of CINES, for his efficient handling of our request for computational time. Figures were created using matplotlib (83), seismic data processing was done in ObsPy (84), and numerical evaluation was done in NumPy and SciPy (85, 86). Funding: S.C.S., A.K., D.G., J.C., A.C.D., G.Z., and N.D. acknowledge support from ETHZ through the ETH+ funding scheme (ETH+2 19-1: “Planet MARS”). S.C.S. acknowledges funding from ETH research grant ETH-10 17-3. W.B.B., A.G.M., M.P.P., and S.E.S. were supported by the NASA InSight mission and funds from the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). D.A. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement 724690). The French teams acknowledge support from CNES as well as Agence Nationale de la Recherche (ANR-14-CE36-0012-02 and ANR-19-CE31-0008-08). A.R. was financially supported by the Belgian PRODEX program managed by the European Space Agency in collaboration with the Belgian Federal Science Policy Office. M.S. wishes to thank SANIMS (RTI2018-095594-B-I00). M.v.D. received support from the ERC under the European Union’s Horizon 2020 program (grant no. 714069). D.S. and C.S. acknowledge funding from ETH research grant ETH-06 17-02. J.C.E.I. acknowledges support from NASA grant 80NSSC18K1633. N.S., D.K., Q.H., R.M., V.L., and A.G.M. acknowledge NASA grant 80NSSC18K1628 for support. V.L. acknowledges support from the Packard Foundation. W.T.P. and C.C. received funding from the UK Space Agency, grant ST/S001239/1. A.H. was funded by the UK Space Agency (grant ST/R002096/1). A.-C.P. acknowledges the financial support and endorsement from the DLR Management Board Young Research Group Leader Program and the Executive Board Member for Space Research and Technology. Author contributions: S.C.S., D.G., S.C., R.F.G., Q.H., D.K., V.L., M.S., N.S., D.S., É.S., C.S., and G.Z. analyzed the seismic data and made ScS arrival time picks. S.C.S., P.L., D.G., Z.X., C.C., and W.T.P. performed the statistical analysis of the observed signals. S.C.S., Q.H., N.S., R.M., and A.G.M. identified the arrivals as ScS waves based on interior models from A.K., H.S., and A.R. A.K., M.D., A.C.D., and H.S. performed the inversions. S.C.S., A.K., P.L., D.G., D.A., J.C.E.I., M.K., C.P., A.-C.P., A.R., T.G., and S.E.S. participated and contributed to the interpretation of the results. Review of the continuous data and detection of marsquakes was done by S.C.S., S.C., G.Z., C.C., N.D., J.C., M.v.D., T.K., M.P., and A.H. with operational support by É.B., C.P., and P.M.D. S.C.S. and A.K. wrote the central part of the paper with contributions from H.S., N.S., D.A., J.C.E.I., A.G.M., A.-C.P., A.R., J.C., and M.v.D. J.C.E.I., R.M., M.K., and V.L. reviewed the contributions to the supplementary materials. The InSight mission is managed by W.B.B., M.P.P., and S.E.S. The SEIS instrument development was led by P.L., D.G., W.T.P., and W.B.B. Supplementary section 1 was written by M.S., D.S., and É.S. with contributions from S.C.S., C.S., and Z.X. Supplementary section 2 was written by D.K. and V.L. with contributions from J.C.E.I. and N.S. Supplementary section 3 was written by M.S. and É.S. Supplementary section 4 was written by R.F.G. with contributions from M.D. Supplementary section 5 was written by Q.H. with contributions from N.S. Supplementary section 6 was written by S.C.S. with contributions from the authors of the other supplements. Supplementary section 7 was written by Z.X. and C.C. with contributions from P.L. and W.T.P. Supplementary section 8 was written by A.K., M.D., A.C.D., and H.S. Supplementary section 9 was written by M.D. Supplementary section 10 was written by A.C.D., A.K., and M.D. Supplementary section 11 was written by D.A. and A.R. with contributions from A.K. Competing interests: The authors declare that they have no competing interests. Data and materials availability: We thank the operators of JPL, SISMOC, MSDS, IRIS-DMC, and PDS for providing SEED SEIS data (87). Three hundred interior models derived in this study are available from MSDS (88)

Resonances and Lander Modes Observed by InSight on Mars (1–9 Hz)

The National Aeronautics and Space Administration’s (NASAs) Interior exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) lander successfully touched down on Mars in November 2018, and, for the first time, a seismometer was deployed on the surface of the planet. The seismic recordings reveal diurnal and seasonal changes of the broadband noise level that are consistent with variations of the local atmospheric conditions. The seismic data include a variety of spectral peaks, which are interpreted as wind-excited,mechanical resonances of the lander, resonances of the subsurface, or artifacts produced in themeasurement system. Understanding the origin of these signals is critical for the detection and characterization of marsquakes as well as for studies investigating the ambient noise. We identify the major spectral peaks up to 9 Hz, corresponding to the frequency range the most relevant to observed marsquakes. We track the variations in frequency, amplitude, and polarization of these peaks over the duration of the mission so far. The majority of these peaks can readily be classified as measurement artifacts or lander resonances (lander modes), of which the latter have a temperature-dependent peak frequency and a wind-sensitive amplitude. Of particular interest is a prominent resonance at 2.4 Hz, which is used to discriminate between seismic events and local noise and is possibly produced by a subsurface structure. In contrast to the lander modes, the 2.4 Hz resonance has distinctly different features: (1) a broad and stable spectral shape, slightly shifted on each component; (2) predominantly vertical energy; (3) temperature-independent peak frequency; (4) comparatively weak amplification by local winds, though there is a slow change in the diurnal and seasonal amplitude; and (5) excitation during all seismic events that excite this frequency band. Based on these observations, we suggest that the 2.4 Hz resonance is the only mode below 9 Hz that could be related to a local ground structureThe authors acknowledge National Aeronautics and Space Administration (NASA), The National Centre for Space Studies of France (CNES), their partner agencies and institutions (UK Space Agency [UKSA], Swiss Space Office [SSO], Deutsches Zentrum für Luft- und Raumfahrt [DLR], Jet Propulsion Laboratory [JPL], Institut du Physique du Globe de Paris Centre National de la Recherche Scientifique [IPGP-CNRS], Eidgenössische Technische Hochschule Zürich [ETHZ], Imperial College London [IC], Max-Planck Institut for Solar System Research [MPS-MPG]), and the flight operations team at JPL, SEIS on Mars Operation Center (SISMOC), Mars SEIS Package Data Service (MSDS), Incorporated Research Institutions for Seismology Data Management Center (IRIS-DMC), and Planetary Data System (PDS) for providing Standard for the Exchange of Earthquake Data (SEED) Seismic Experiment for Interior Structure (SEIS) data. We acknowledge funding from (1) Swiss State Secretariat for Education, Research, and Innovation (SEFRI project “MarsQuake Service-Preparatory Phase”), (2) ETH Research grant ETH-06 17-02, and (3) ETH+02 19-1: Planet MARS. The Swiss contribution in implementation of the SEIS electronics was made possible through funding from the federal Swiss Space Office (SSO), the contractual and technical support of the European Space Agency – Programme de Développement d'Expériences scientifiques (ESA-PRODEX) office. The French authors acknowledge the French Space Agency CNES and French National Agency for Research (ANR) (ANR-14-CE36-0012-02 and ANR‐19-CE31-0008-08) for support in the Science analysis. This is Interior exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) contribution 202.Peer reviewe

The mechanical properties of the Martian soil at the InSight landing site

The InSight mission is a NASA geophysical mission aimed at better understanding the structure of Mars and of the other rocky plan-ets of the solar system. To do so, various instruments are used, including a very sensitive seismometer (SEIS) and a dynamic self-penetrating heat probe (HP3) that have been placed on the Mars surface by the Instrument Deployment Arm (IDA). Besides geophys-ical data (which have definitely enriched and completed existing knowledge on the structure of Mars), the InSight instruments, togeth-er with orbiter observations and tests carried out on the soil with the IDA, have significantly increased the knowledge of the geologi-cal and geotechnical characteristics of the surface material at the InSight site, which is made up of a basaltic sand. In-situ data were also successfully compared with terrestrial previous estimates from terrestrial lab tests, carried out on various soil simulants. Small strain (elastic) parameters at small strains were derived from wave velocity measurements between the self-penetrating probe and the seismometer. Strength data were derived from both IDA operations and penetration data. The soil includes some pebbles within a somewhat cohesive sandy matrix, limiting the heat probe penetration to only 40 cm length. Thermal data were also obtained, allowing for some thermo-elastic modelling of the effect of the Phobos (one of the “Moons” of Mars) eclipses. Elastic data were also derived from the effects of wind on the ground, detected by SEIS

The InSight HP3 Penetrator (Mole) on Mars: Soil Properties Derived from the Penetration Attempts and Related Activities

The NASA InSight Lander on Mars includes the Heat Flow and Physical Properties Package HP3 to measure the surface heat flow of the planet. The package uses temperature sensors that would have been brought to the target depth of 3–5 m by a small penetrator, nicknamed the mole. The mole requiring friction on its hull to balance remaining recoil from its hammer mechanism did not penetrate to the targeted depth. Instead, by precessing about a point midway along its hull, it carved a 7 cm deep and 5–6 cm wide pit and reached a depth of initially 31 cm. The root cause of the failure – as was determined through an extensive, almost two years long campaign – was a lack of friction in an unexpectedly thick cohesive duricrust. During the campaign – described in detail in this paper – the mole penetrated further aided by friction applied using the scoop at the end of the robotic Instrument Deployment Arm and by direct support by the latter. The mole tip finally reached a depth of about 37 cm, bringing the mole back-end 1–2 cm below the surface. It reversed its downward motion twice during attempts to provide friction through pressure on the regolith instead of directly with the scoop to the mole hull. The penetration record of the mole was used to infer mechanical soil parameters such as the penetration resistance of the duricrust of 0.3–0.7 MPa and a penetration resistance of a deeper layer (> 30 cm depth) of 4.9±0.4 MPa. Using the mole’s thermal sensors, thermal conductivity and diffusivity were measured. Applying cone penetration theory, the resistance of the duricrust was used to estimate a cohesion of the latter of 2–15 kPa depending on the internal friction angle of the duricrust. Pushing the scoop with its blade into the surface and chopping off a piece of duricrust provided another estimate of the cohesion of 5.8 kPa. The hammerings of the mole were recorded by the seismometer SEIS and the signals were used to derive P-wave and S-wave velocities representative of the topmost tens of cm of the regolith. Together with the density provided by a thermal conductivity and diffusivity measurement using the mole’s thermal sensors, the elastic moduli were calculated from the seismic velocities. Using empirical correlations from terrestrial soil studies between the shear modulus and cohesion, the previous cohesion estimates were found to be consistent with the elastic moduli. The combined data were used to derive a model of the regolith that has an about 20 cm thick duricrust underneath a 1 cm thick unconsolidated layer of sand mixed with dust and above another 10 cm of unconsolidated sand. Underneath the latter, a layer more resistant to penetration and possibly containing debris from a small impact crater is inferred. The thermal conductivity increases from 14 mW/m K to 34 mW/m K through the 1 cm sand/dust layer, keeps the latter value in the duricrust and the sand layer underneath and then increases to 64 mW/m K in the sand/gravel layer below