Sources Of Systematic Error Research Articles

Mountain permafrost degradation documented through a network of permanent electrical resistivity tomography sites

Abstract. Mountain permafrost is sensitive to climate change and is expected to gradually degrade in response to the ongoing atmospheric warming trend. Long-term monitoring of the permafrost thermal state is a key task, but problematic where temperatures are close to 0 ∘C because the energy exchange is then dominantly related to latent heat effects associated with phase change (ice–water), rather than ground warming or cooling. Consequently, it is difficult to detect significant spatio-temporal variations in ground properties (e.g. ice–water ratio) that occur during the freezing–thawing process with point scale temperature monitoring alone. Hence, electrical methods have become popular in permafrost investigations as the resistivities of ice and water differ by several orders of magnitude, theoretically allowing a clear distinction between frozen and unfrozen ground. In this study we present an assessment of mountain permafrost evolution using long-term electrical resistivity tomography monitoring (ERTM) from a network of permanent sites in the central Alps. The time series consist of more than 1000 datasets from six sites, where resistivities have been measured on a regular basis for up to 20 years. We identify systematic sources of error and apply automatic filtering procedures during data processing. In order to constrain the interpretation of the results, we analyse inversion results and long-term resistivity changes in comparison with existing borehole temperature time series. Our results show that the resistivity dataset provides valuable insights at the melting point, where temperature changes stagnate due to latent heat effects. The longest time series (19 years) demonstrates a prominent permafrost degradation trend, but degradation is also detectable in shorter time series (about a decade) at most sites. In spite of the wide range of morphological, climatological, and geological differences between the sites, the observed inter-annual resistivity changes and long-term tendencies are similar for all sites of the network.

A VLBI delay model for gravitational deformations of the Onsala 20 m radio telescope and the impact on its global coordinates

Deformations of the reflectors of radio telescopes used in geodetic and astrometric VLBI observations belong to the class of systematic error sources which affect the estimated position of the telescope and which necessitates correction at the observation level. The determination of the gravitationally induced deformations requires some effort and needs specific modeling of the impact on the VLBI delay observables. This has been exercised on the Onsala 20 m radio telescope. In this publication, we present an elevation-dependent model for the contributions of the gravitational deformations to the delay observables for application in VLBI data analysis. New is that thermal expansion in some of the contributing components need to be applied also to the gravitational deformation effects. A further novelty is that we can substantiate the validity of and the need for these corrections. Concerning the validity we show that the empirical model used by astronomical colleagues for deliberately shifting the sub-reflector for gain optimization, exactly (within 0.5 mm RMS) matches the measured gravitationally induced displacement of the sub-reflector plus the change in focal length. The other evidence is the impact on the vertical component of the telescope’s coordinates of − 6.1 mm, which reduces the discrepancy determined in the computations of the ITRF2014 to 1.7 mm.

Resolved and Integrated Stellar Masses in the SDSS-IV/MaNGA Survey. II. Applications of PCA-based Stellar Mass Estimates

Abstract A galaxy’s stellar mass is one of its most fundamental properties, but it remains challenging to measure reliably. With the advent of very large optical spectroscopic surveys, efficient methods that can make use of low signal-to-noise spectra are needed. With this in mind, we created a new software package for estimating effective stellar mass-to-light ratios that uses a principal component analysis (PCA) basis set to optimize the comparison between observed spectra and a large library of stellar population synthesis models. In Paper I, we showed that with a set of six PCA basis vectors we could faithfully represent most optical spectra from the Mapping Nearby Galaxies at APO (MaNGA) survey, and we tested the accuracy of our M/L estimates using synthetic spectra. Here, we explore sources of systematic error in our mass measurements by comparing our new measurements to data from the literature. We compare our stellar mass surface density estimates to kinematics-derived dynamical mass surface density measurements from the DiskMass Survey and find some tension between the two that could be resolved if the disk scale heights used in the kinematic analysis were overestimated by a factor of ∼1.5. We formulate an aperture-corrected stellar mass catalog for the MaNGA survey, and compare to previous stellar mass estimates based on multiband optical photometry, finding typical discrepancies of 0.1 dex. Using the spatially resolved MaNGA data, we evaluate the impact of estimating total stellar masses from spatially unresolved spectra, and we explore how the biases that result from unresolved spectra depend upon the galaxy’s dust extinction and star formation rate. Finally, we describe an SDSS Value-Added Catalog that will include both spatially resolved and total (aperture-corrected) stellar masses for MaNGA galaxies.

Tests of acoustic scale shifts in halo-based mock galaxy catalogues

ABSTRACT We utilize mock catalogues from high-accuracy cosmological N-body simulations to quantify shifts in the recovery of the acoustic scale that could potentially result from galaxy clustering bias. The relationship between galaxies and dark matter haloes presents a complicated source of systematic errors in modern redshift surveys, particularly when aiming to make cosmological measurements to sub-per cent precision. Apart from a scalar, linear bias parameter accounting for the density contrast ratio between matter tracers and the true matter distribution, other types of galaxy bias, such as assembly and velocity biases, may also significantly alter clustering signals from small to large scales. We create mocks based on generalized halo occupation populations of 36 periodic boxes from the abacus cosmosrelease, and test various biased models along with an unbiased base case in a total volume of $48 \, h^{-3} \, {\rm Gpc}^{3}$. Two reconstruction methods are applied to galaxy samples and the apparent acoustic scale is derived by fitting the two-point correlation function multipoles. With respect to the baseline, we find a 0.3 per cent shift in the line-of-sight acoustic scale for one variation in the satellite galaxy population, and we find a 0.7 per cent shift for an extreme level of velocity bias of the central galaxies. All other bias models are consistent with zero shift at the 0.2 per cent level after reconstruction. We note that the bias models explored are relatively large variations, producing sizeable and likely distinguishable changes in small-scale clustering, the modelling of which would further calibrate the baryon acoustic oscillations standard ruler.

Precise DNA Concentration Measurements with Nanopores by Controlled Counting.

Using a solid-state nanopore to measure the concentration of clinically relevant target analytes, such as proteins or specific DNA sequences, is a major goal of nanopore research. This is usually achieved by measuring the capture rate of the target analyte through the pore. However, progress is hindered by sources of systematic error that are beyond the level of control currently achievable with state-of-the-art nanofabrication techniques. In this work, we show that the capture rate process of solid-state nanopores is subject to significant sources of variability, both within individual nanopores over time and between different nanopores of nominally identical size, which are absent from theoretical electrophoretic capture models. We experimentally reveal that these fluctuations are inherent to the nanopore itself and make nanopore-based molecular concentration determination insufficiently precise to meet the standards of most applications. In this work, we present a simple method by which to reduce this variability, increasing the reliability, accuracy, and precision of single-molecule nanopore-based concentration measurements. We demonstrate controlled counting, a concentration measurement technique, which involves measuring the simultaneous capture rates of a mixture of both the target molecule and an internal calibrator of precisely known concentration. Using this method on linear DNA fragments, we show empirically that the requirements for precisely controlling the nanopore properties, including its size, height, geometry, and surface charge density or distribution, are removed while allowing for higher-precision measurements. The quantitative tools presented herein will greatly improve the utility of solid-state nanopores as sensors of target biomolecule concentration.

Impact of GPS receiver antenna GRAPHIC residual variations on single-frequency orbit determination of LEO satellites

Single-frequency (SF) precise orbit determination (POD) using space-borne Global Positioning System (GPS) measurements is a prerequisite for the success of many low-cost small/micro low Earth orbit (LEO) satellite missions. The first-order ionospheric effects are usually eliminated by group and phase ionospheric correction (GRAPHIC) combinations. GPS receiver antenna GRAPHIC residual variations (GRVs) are important systematic error sources in SF orbit determination. Azimuth and elevation dependent GRVs are estimated and obtained based on the GRAPHIC combination residuals in an in-flight calibration. One month of data from GRACE-A, GRACE-B, CHAMP and HY-2A satellites is used to assess the potential of receiver antenna GRVs in SF orbit determination. It is the first time to study the impact of receiver antenna GRVs on SF orbit determination for different LEO satellites, which exhibit different altitudes and data qualities. The impact of receiver antenna GRVs on SF orbit determination is significant. The use of in-flight determined receiver antenna GRVs leads to a better consistency between SF and dual-frequency POD solutions. The improvements are more obvious for GRACE-A and CHAMP satellites, whose receiver antenna GRV patterns demonstrate clear characteristics of systematic deviations. After correcting the receiver antenna GRVs, the root-mean-square of satellite laser ranging validation residuals are 3.11 cm, 2.31 cm, 2.86 cm and 5.29 cm for GRACE-A, GRACE-B, CHAMP and HY-2A satellites, respectively, which are reduced by 11.1%, 4.6%, 14.6% and 4.7%, respectively. At last, a set of a priori GDV corrections of GPS transmitter antennas are used in SF orbit determination and its effects on receiver antenna GRVs estimation and SF orbit determination are analyzed. Applying these corrections can slightly improve the SF orbit quality of GRACE-A satellite.

Toward precision radial velocity measurements using Echelle spectrograph at Vainu Bappu Telescope (Erratum)

The Echelle spectrograph operating at Vainu Bappu Telescope is a general purpose instrument designed for high-resolution spectroscopy. It is being considered for precision Doppler measurements without altering the existing design and basic usage. However, the design level limitations and environmental perturbations are a major source of instability and systematic errors. As a result, a small Doppler signal in the stellar spectra is completely swamped by the large and uncontrolled instrumental drift. We discuss some of the remedial measures we took to improve the radial velocity performance of the spectrograph. We show that an autoguider assembly has greatly reduced the mechanical jitter of the star image at the fiber input, making the illumination of the spectrograph slit at the other end stable. We have also installed an iodine absorption cell to track and eliminate the instrumental drifts to facilitate precision radial velocity observations. Furthermore, we have developed a generic algorithm that uses iodine exposures to extract the stellar radial velocities without the need for the complex forward modeling. Our algorithm is not accurate to the level of traditional iodine technique. However, it is convenient to use on a low-cost general-purpose spectrograph targeting a moderate radial velocity (RV) precision at a few 10 to 100 ms − 1 level. Finally, we have demonstrated the usefulness of our approach by measuring the RV signal of a well-known short-period, planet-hosting star.

Enumeration of lactic acid bacteria: lacuna and improvement areas highlighted by proficiency testing

During the 2011 to 2018 food microbiology proficiency testing (PT) schemes organized by REQUASUD, a systematic analytical issue was detected. For the enumeration of the lactic acid bacteria (LAB), laboratories carrying out the same analytical method (ISO 15214) yielded completely incoherent results while analysing naturally contaminated samples (raw milk, smoked salmon and ham sausage), leading to an atypically large distribution of the PT results. A comprehensive study of these atypical PT results provided insight into the source of systematic errors affecting the LAB enumeration. The main sources of analytical variability turned out to be linked to the ISO 15214:1998 standard. To better harmonize the analytical results, practical improvements can be proposed for the revision of this standard, mainly: the addition of precise criteria for the colony count, a restriction of the allowed incubation conditions and the use of a more selective culture medium (e.g. supplemented with sorbate) to limit the growth of interfering colonies. PT is a privileged observation post to highlight such analytical issues, which would otherwise remain unnoticed. Whenever an unusual distribution of PT results is observed (e.g. high dispersion or non-normal distribution of the values), it is the responsibility of the PT provider to try to identify the causes of non-normality, in a perspective of method improvement. The statistical analysis of atypical PT results requires specific attention: ignoring the non-normality of PT results when it occurs can lead to set an erroneous assigned value, unfairly penalizing participants.

Toward precision radial velocity measurements using Echelle spectrograph at Vainu Bappu Telescope

The Echelle spectrograph operating at Vainu Bappu Telescope (VBT) is a general purpose instrument designed for high resolution spectroscopy. It is being considered for precision Doppler measurements without altering the existing design and basic usage. However, the design level limitations and environmental perturbations are a major source of instability and systematic errors. As a result, a small Doppler signal in the stellar spectra is completely swamped by the large and uncontrolled instrumental drift. In this paper, we discuss some of the remedial measures we took to improve the radial velocity performance of the spectrograph. We show that a new auto-guider assembly has greatly reduced the mechanical jitter of the star image at the fibre input, making the illumination of the spectrograph slit at the other end stable. We have also installed an iodine absorption cell to track and eliminate the instrumental drifts to facilitate precision radial velocity observations. Furthermore, we have developed a generic algorithm that uses iodine exposures to extract the stellar radial velocities without the need for the complex forward modeling. Our algorithm is not accurate to the level of traditional iodine technique. However it is convenient to use on a low-cost general-purpose spectrograph targeting a moderate Radial Velocity (RV) precision at a few 10-100~$\textrm{ms}^{-1}$ level. Finally, we have demonstrated the usefulness of our approach by measuring the RV signal of a well known short-period, planet-hosting star.

Analysis of artifacts and systematic errors of the Iranian Seismological Center’s earthquake catalog

This study reviews the history of seismometry in Iran and specifically the evolution of Iranian Seismological Center’s (IRSC) seismic network and investigates the artifacts and systematic errors of this center’s earthquake catalog. Our analysis indicates instability of magnitude estimation in the IRSC catalog to the extent that in the western and eastern parts of Iran, events with the same USGS reported mb magnitude could result in MN values 0.3 units apart. This catalog is contaminated with quarry and mine blasts, in which about 19% of the reported events are most likely not tectonic earthquakes. In addition, heterogeneity of magnitude of completeness as a function of space and time is observed. While Mc has gradually improved since 2006, its reduction in different parts of the country varies between 0 to 0.5 units of magnitude. In addition to artifacts, more than 54% of the reported events were located using a simplified velocity model and need to be relocated using more accurate velocity models. Moreover, in the hypocenter determination of about 7% of earthquakes, at least data from one station with wrong coordinates was employed. For these two groups of events, a clear dependence exists between the azimuthal gap and the value of the observed shift in the location parameters; with increasing the azimuthal gap, the shift increases. Investigations on the manually picked phases in the IRSC catalog show a large number of phase misidentification cases which are the other source of systematic errors. Examining the depth reported for events associated with mine blasts in a region in southern Iran implies systematic errors and high overestimation of depth for these events. The reported depth for most of these blasts is more than 10 km.

Systematic error in manometric measurement of biochemical methane potential: Sources and solutions

This work focused on identification and quantification of systematic sources of error in manometric measurement of biochemical methane potential (BMP). Error was determined by comparison to gravimetric measurements and direct measurement of leakage. One out of three types of septa leaked above 1 bar (gauge) headspace pressure, losing 25 to 30% of biogas produced. But manometric BMP showed a negative bias even in the absence of leakage. Maximum error was 24% from 160 mL bottles with 40 mL of headspace (headspace fraction of 0.25). Error decreased with increasing headspace fraction, and was small (3%) for a headspace fraction of 0.75, showing that a high headspace volume is the best approach for minimizing error. Relative error in CH4 production measurement increased with headspace pressure as well, but controlling pressure alone is not sufficient for minimizing error. Calculations showed that observed error may be due to volatilization of CH4 during venting as well as inaccurate headspace volume determination, although these sources do not completely explain the magnitude of error observed. Measurement of biogas composition before and after venting showed that CO2 volatilization can occur, but is probably a minor source of error. Calculations showed that error in estimation of ambient pressure or headspace temperature had only minor effects (<3%). Gravimetric measurements, which were unaffected by leakage and insensitive to error in estimation of headspace pressure, temperature or volume, can provide a simple check on manometric results, or a complete replacement.

Toward Accurate Hydrogen Bonds by Scalable Quantum Monte Carlo.

Single-determinant (SD) fixed-node diffusion Monte Carlo (FNDMC) gains popularity as a benchmark method scalable to large noncovalent systems, although its accuracy limits are not yet fully mapped out. We report on an interesting example of significant SD FNDMC accuracy variations in middle-sized hydrogen-bonded dimer complexes, formic acid (FA) vs methanediol (MD), distinct by the maximum bond order (2 vs 1). While the traditional SD FNDMC schemes based on bias cancellation are capable of achieving benchmark (2%) accuracy for MD, this has not been the case for FA. We identify the leading systematic error source in energy differences and show that suitably designed Jastrow factors enable SD FNDMC to reach the reference accuracy for FA. This work clearly illustrates the varying accuracy of the present-day SD FNDMC at the 0.1 kcal/mol scale for a particular set of systems but also points out promising routes toward alleviation of these shortcomings, still within the single-reference framework.

A Critical Appraisal of the Placement of Xiphosura (Chelicerata) with Account of Known Sources of Phylogenetic Error.

Horseshoe crabs (Xiphosura) are traditionally regarded as sister group to the clade of terrestrial chelicerates (Arachnida). This hypothesis has been challenged by recent phylogenomic analyses, but the non-monophyly of Arachnida has consistently been disregarded as artifactual. We re-evaluated the placement of Xiphosura among chelicerates using the most complete phylogenetic data set to date, expanding outgroup sampling, and including data from whole genome sequencing projects. In spite of uncertainty in the placement of some arachnid clades, all analyses show Xiphosura consistently nested within Arachnida as the sister group to Ricinulei (hooded tick spiders). It is apparent that the radiation of arachnids is an old one and occurred over a brief period of time, resulting in several consecutive short internodes, and thus is a potential case for the confounding effects of incomplete lineage sorting (ILS). We simulated coalescent gene trees to explore the effects of increasing levels of ILS on the placement of horseshoe crabs. In addition, common sources of systematic error were evaluated, as well as the effects of fast-evolving partitions and the dynamics of problematic long branch orders. Our results indicated that the placement of horseshoe crabs cannot be explained by missing data, compositional biases, saturation, or ILS. Interrogation of the phylogenetic signal showed that the majority of loci favor the derived placement of Xiphosura over a monophyletic Arachnida. Our analyses support the inference that horseshoe crabs represent a group of aquatic arachnids, comparable to aquatic mites, breaking a long-standing paradigm in chelicerate evolution and altering previous interpretations of the ancestral transition to the terrestrial habitat. Future studies testing chelicerate relationships should approach the task with a sampling strategy where the monophyly of Arachnida is not held as the premise.

A congruent topology for deep gastropod relationships.

Gastropod molluscs are among the most diverse and abundant animals in the oceans, and are successful colonizers of terrestrial and freshwater environments. Past phylogenetic efforts to resolve gastropod relationships resulted in a range of conflicting hypotheses. Here, we use phylogenomics to address deep relationships between the five major gastropod lineages—Caenogastropoda, Heterobranchia, Neritimorpha, Patellogastropoda and Vetigastropoda—and provide one congruent and well-supported topology. We substantially expand taxon sampling for outgroups and for previously underrepresented gastropod lineages, presenting new transcriptomes for neritimorphs and patellogastropods. We conduct analyses under maximum-likelihood, Bayesian inference and a coalescent-based approach, accounting for the most pervasive sources of systematic errors in large datasets: compositional heterogeneity, site heterogeneity, heterotachy, variation in evolutionary rates among genes, matrix completeness, outgroup choice and gene tree conflict. We find that vetigastropods and patellogastropods are sister taxa, and that neritimorphs are the sister group to caenogastropods and heterobranchs. We name these two major unranked clades Psilogastropoda and Angiogastropoda, respectively. We additionally provide the first genomic-scale data for internal relationships of neritimorphs and patellogastropods. Our results highlight the need for reinterpreting the evolution of morphological and developmental characters in gastropods, especially for inferring their ancestral states.

Evolution of the Stellar Mass Function and Infrared Luminosity Function of Galaxies since z = 1.2

Abstract We measured evolution of the K-band luminosity function and stellar mass function (SMF) for red and blue galaxies at z &lt; 1.2 using a sample of 353 594 I &lt; 24 galaxies in 8.26 square degrees of Boötes. We addressed several sources of systematic and random error in measurements of total galaxy light, photometric redshift, and absolute magnitude. We have found that the K-band luminosity density for both red and blue galaxies increased by a factor of 1.2 from z ∼ 1.1 to z ∼ 0.3, while the most luminous red (blue) galaxies decreased in luminosity by 0.19(0.33) mag or ×0.83(0.74). These results are consistent with z &lt; 0.2 studies, while our large sample size and area result in smaller Poisson and cosmic variance uncertainties than most z &gt; 0.4 luminosity and mass function measurements. Using an evolving relation for K-band mass-to-light ratios as a function of (B−V) color, we found a slowly decreasing rate of growth in red galaxy stellar mass density of ×2.3 from z ∼ 1.1 to z ∼ 0.3, indicating a slowly decreasing rate of migration from the blue cloud to the red sequence. Unlike some studies of the SMF, we find that massive red galaxies grow by a factor of ×1.7 from z ∼ 1.1 to z ∼ 0.3, with the rate of growth due to mergers decreasing with time. These results are comparable with measurements of merger rates and clustering, and they are also consistent with the red galaxy stellar mass growth implied by comparing K-band luminosity evolution with the fading of passive stellar population models.

Analysis of time-lapse data error in complex conductivity imaging to alleviate anthropogenic noise for site characterization

Previous studies have demonstrated the potential benefits of the complex conductivity (CC) imaging over electrical resistivity tomography for an improved delineation of hydrocarbon-impacted sites and accompanying biogeochemical processes. However, time-lapse CC field applications are still rare, in particular for measurements performed near anthropogenic structures such as buried pipes or tanks, which are typically present at contaminated sites. To fill this gap, we have developed CC imaging (CCI) results for monitoring data collected in Trecate (northwest Italy), a site impacted by a crude oil spill. Initial imaging results reveal only a poor correlation with seasonal variations of the groundwater table at the site (approximately 6 m). However, it is not clear to which extend such results are affected by anthropogenic structures present at the site. To address this, we performed a detailed analysis of the misfit between direct and reciprocal time-lapse differences. Based on this analysis, we were able to discriminate spatial and temporal sources of systematic errors, with the latter commonly affecting measurements collected near anthropogenic structures. Following our approach, CC images reveal that temporal changes in the electrical properties correlate well with seasonal fluctuations in the groundwater level for areas free of contaminants, whereas contaminated areas exhibit a constant response over time characterized by a relatively high electrical conductivity and a negligible polarization effect. In accordance with a recent mechanistic model, such a response can be explained by the presence of immiscible fluids (oil and air) forming a continuous film through the micro and macropores, hindering the development of ion-selective membranes and membrane polarization. Our results demonstrate the applicability of CCI for an improved characterization of hydrocarbon-contaminated areas, even in areas affected by cultural noise.

Quantifying Uncertainty from Mass-Peak Overlaps in Atom Probe Microscopy.

There are many sources of random and systematic error in composition quantification by atom probe microscopy, often, however, only statistical error is reported. Significantly larger errors can occur from the misidentification of ions and overlaps or interferences of peaks in the mass spectrum. These overlaps can be solved using maximum likelihood estimation (MLE), improving the accuracy of the result, but with an unknown effect on the precision. An analytical expression for the uncertainty of the MLE solution is presented and it is demonstrated to be much more accurate than the existing methods. In one example, the commonly used error estimate was five times too small.Literature results containing overlaps most likely underestimate composition uncertainty because of the complexity of correctly dealing with stochastic effects and error propagation. The uncertainty depends on the amount of overlapped intensity, for example being ten times worse for the CO/Fe overlap than the Cr/Fe overlap. Using the methods described here, accurate estimation of error, and the minimization of this could be achieved, providing a key milestone in quantitative atom probe. Accurate estimation of the composition uncertainty in the presence of overlaps is crucial for planning experiments and scientific interpretation of the measurements.

Assessing the integrity of soil erosion in different patch covers in semi-arid environment

Soil erosion accelerates the degradation of semiarid ecosystems. How to explain the erosion processes is increasingly attracting scientists’ and practitioners’ attention. In this study, we hypothesized the intensity and uncertainty of runoff and sediment events as the ecological function of soil erosion by using structural equation modeling (SEM), and integrated observed influencing factors to represent the ecological structure of soil erosion. We further assessed the interactions of ecological structures and functions in four typical patch covers containing bare patch (B type), Andropogon patch (G type), Artemisia coparia patch (H type) and Spiraea pubescens patch (J type) in the Loess Plateau over three rainy seasons. We found that (1) the highest and lowest probabilities of runoff (approaching to 0.37 and 0.22) and sediment (approaching to 0.27 and 0.03) events were in B and J types respectively. B type produced the highest runoff coefficients (0.004) and yielded 2–3 times more sediment than other three vegetation patch covers. (2) Antecedent soil moisture and crown width were two relative more crucial indicators to simultaneously affect the uncertainty and intensity of soil erosion in different patch cover patterns. (3) Soil saturated hydraulic conductivity connected the soil and plant latent variables to indicate the complexity of ecological structure. (4) The measurement error of sediment yield became the main source of system error of the soil erosion assessment by SEM. These results suggest that the uncertainty of runoff and sediment event was an important descriptor to improve the interpretation of ecological function of soil erosion. The logistic regression and SEM form a new analysis framework to explore the interaction between ecological structure and function of soil erosion. This framework could enhance the understanding of erosion processes, and be beneficial to managing the restoration vegetation and utilizing the available water and soil resources in semiarid environment.

Magnetic field effects on the proton EDM in a continuous all-electric storage ring

The electric dipole moment of the proton can be searched in an electric storage ring by measuring the spin precession rate of the proton beam on the vertical plane. In the ideal case, the spin precession originates from the coupling between the electric field and the electric dipole moment. In a more realistic scenario, the magnetic field becomes a major systematic error source as it couples with the magnetic dipole moment in a similar way. The beam can see the magnetic field in various configurations which include direction, time dependence, etc. For instance, geometric phase effect is observed when the beam sees the field at different directions and phases periodically. We have simulated the effect of magnetic fields in major independent scenarios and found consistent results with the analytical estimations of the static magnetic field cases. We have set a limit for the magnetic field in each scenario and proposed solutions to avoid systematic errors from magnetic fields.

Calibrating long-period variables as standard candles with machine learning

Variable stars with well-calibrated period-luminosity relationships provide accurate distance measurements to nearby galaxies and are therefore a vital tool for cosmology and astrophysics. While these measurements typically rely on samples of Cepheid and RR-Lyrae stars, abundant populations of luminous variable stars with longer periods of $10 - 1000$ days remain largely unused. We apply machine learning to derive a mapping between lightcurve features of these variable stars and their magnitude to extend the traditional period-luminosity (PL) relation commonly used for Cepheid samples. Using photometric data for long period variable stars in the Large Magellanic cloud (LMC), we demonstrate that our predictions produce residual errors comparable to those obtained on the corresponding Cepheid population. We show that our model generalizes well to other samples by performing a blind test on photometric data from the Small Magellanic Cloud (SMC). Our predictions on the SMC again show small residual errors and biases, comparable to results that employ PL relations fitted on Cepheid samples. The residual biases are complementary between the long period variable and Cepheid fits, which provides exciting prospects to better control sources of systematic error in cosmological distance measurements. We finally show that the proposed methodology can be used to optimize samples of variable stars as standard candles independent of any prior variable star classification.