Lomb-Scargle Research Articles

Monitoring Non-Linear Ground Motion above Underground Gas Storage Using GNSS and PSInSAR Based on Sentinel-1 Data

Several methods allow accurate measurement of terrain surface motions. Global navigation satellite systems (GNSSes) and interferometry with synthetic aperture radar (InSAR) stand out in terms of measurement accuracy among them. In principle, both methods make it possible to evaluate a three-dimensional vector of the motion of points on the terrain surface. In this work, we dealt with the evaluation of motions in the up–down (U–D) and east–west direction (E–W) over underground gas storage (UGS) from InSAR. One crucial step in breaking down PSInSAR line of sight (LOS) measurements to U–D and E–W components is getting time series derived from individual tracks to the same time frame. This is usually performed by interpolation, but we used an innovative approach: we analyzed individual time series using the Lomb–Scargle periodogram (LSP), which is suitable for periodic noisy and irregularly sampled data; we selected the most significant period, created LSP models, and used them instead of the original time series. Then, it was possible to derive time series values for any arbitrary time step. To validate the results, we installed one GNSS receiver in the Tvrdonice UGS test area to perform independent measurements. The results show a good agreement in the evaluation of motions by both methods. The correlation coefficient between horizontal components from both PSInSAR and GNSS was 0.95 in the case of the E–W component, with an RMSE of 1.75 mm; for U–D they were 0.78 and 2.35 mm, respectively. In addition to comparing the motions in the U–D and E–W directions, we also created a comparison by converting GNSS measurements to a line of sight of the Sentinel-1 satellite to evaluate the conformity of InSAR and GNSS measurements. Based on descending track, the correlation coefficient between LOS from both methods is, on average, 0.97, with an RMSE of 2.70 mm.

Variability of Equatorial Ionospheric Bubbles over Planetary Scale: Assessment of Terrestrial Drivers

Nighttime F-region field-aligned irregularities (FAIs) associated with equatorial plasma bubbles (EPBs) are impacted by terrestrial factors, such as solar irradiance and geomagnetic activity. This paper examines the impact of the planetary-scale periodic variability of terrestrial processes on EPB activity. Continual observations of the Equatorial Atmosphere Radar (EAR) have been utilized to derive the intra-seasonal variability of nighttime F-region FAIs in the context of the terrestrial factors mentioned above. A periodicity analysis using wavelet and Lomb–Scargle (LS) spectral analysis indicated significant amplitudes of the long-period planetary-scale variability in the F-region FAI signal-to-noise ratio (SNR), 10.7 cm flux, and geomagnetic indices, as well as a shorter period of variability. Interestingly, a careful inspection of the time series indicated the planetary-scale variability of F-region FAIs to be reasonably out of phase with the periodic geomagnetic variability. EPB occurrence and the FAI signal-to-noise ratio presented a systematic decrease with an increase in the level of geomagnetic activity. Non-transient quiet-time geomagnetic activity has been found to suppress both the occurrence as well as the strength of F-region FAIs. The impacts of planetary-scale geomagnetic activity appear to be non-identical in the summer and equinoctial EPBs. The results highlight the importance of periodic terrestrial processes in driving the planetary-scale variability of EPBs.

A 3.8 yr optical quasi-periodic oscillations in blue quasar SDSS J132144+033055 through combined light curves from CSS and ZTF

ABSTRACT In the manuscript, a 3.8 yr optical quasi-periodic oscillations (QPOs) is reported in blue quasar SDSS J132144+033055 (= SDSS J1321) at z = 0.269, based on 16.3yr-long light curve from both CSS and ZTF directly described by a sinusoidal function. The 3.8 yr QPOs can be confirmed through the Generalized Lomb–Scargle periodogram with confidence level higher than 5σ, through properties of the phase-folded light curve and the WWZ technique. Moreover, the collected Pan-STARRS light curves well follow the sinusoidal function described best fitting results to the Catalina Sky Survey (CSS) and Catalina Sky Survey (ZTF) light curves. The optical QPOs strongly indicate a central binary black hole (BBH) system in SDSS J1321, with expected space separation smaller than 0.018 pc, through the estimated upper limit of total BH mass 3.3 × 109 M⊙ through the correlation between BH mass and continuum luminosity. Meanwhile, we check disc precession applied to explain the optical QPOs. However, under the disc precession assumption, the determined optical emission regions from central BH have sizes about 37RG similar as the sizes 35RG of the expected NUV emission regions through the correlation between disc size and BH mass, indicating the disc precession is not preferred. And due to undetected radio emissions, jet precession can be ruled out. Furthermore, only 0.1 per cent probability can determined as the QPOs mis-detected through CAR process randomly created light curves related to intrinsic AGN activities, re-confirming the optical QPOs with significance level higher than 3σ. Therefore, combining long-term light curves from CSS and ZTF can lead to more QPOs candidates in the near future.

Do Cellular Automaton Avalanche Models Simulate the Quasi-periodic Pulsations of Solar Flares?

Quasi-periodic pulsations (QPPs) with various periods that originate in the underlying magnetohydrodynamic processes of flaring structures are detected repeatedly in solar flare emissions. We apply a 2D cellular automaton (CA) avalanche model to simulate QPPs as a result of a repetitive load/unload mechanism. We show that the frequent occurrence of magnetic reconnections in a flaring loop could induce quasi-periodic patterns in the detected emissions. We find that among 21,070 simulated flares, 813 events last over 50 s, scaled with the temporal resolution of the Yohkoh Hard X-ray Telescope, and about 70% of these rather long-lasting events exhibit QPPs. We also illustrate that the applied CA model provides a wide range of periodicities for QPPs. Furthermore, we observe the presence of multiple periods in nearly 50% of the cases by applying the Lomb–Scargle periodogram. A lognormal distribution is fitted to the unimodal distribution of the periods as a manifestation of an underlying multiplicative mechanism that typifies the effect of the system’s independently varying parameters. The global maximum of the periods’ lognormal distribution is located at 29.29 ± 0.67 s. We compare statistics of the simulated QPPs with parameters of the host flares and discuss the impacts of flare properties on the periods of QPPs. Considering the intrinsic characteristic of CA models, namely the repetitive load/unload mechanism, and the obtained pieces of evidence, we suggest that CA models may generate QPPs. We also examine the applicability of autoregressive integrated moving average models to describe the simulated and observed QPPs.

LMD and Lomb–Scargle power spectrum variability analysis of quasars

LMD and Lomb–Scargle power spectrum variability analysis of quasars

Searching for Quasi-periodic Oscillations in Astrophysical Transients Using Gaussian Processes

Analyses of quasi-periodic oscillations (QPOs) are important to understanding the dynamic behavior in many astrophysical objects during transient events like gamma-ray bursts, solar flares, magnetar flares, and fast radio bursts. Astrophysicists often search for QPOs with frequency-domain methods such as (Lomb–Scargle) periodograms, which generally assume power-law models plus some excess around the QPO frequency. Time-series data can alternatively be investigated directly in the time domain using Gaussian process (GP) regression. While GP regression is computationally expensive in the general case, the properties of astrophysical data and models allow fast likelihood strategies. Heteroscedasticity and nonstationarity in data have been shown to cause bias in periodogram-based analyses. GPs can take account of these properties. Using GPs, we model QPOs as a stochastic process on top of a deterministic flare shape. Using Bayesian inference, we demonstrate how to infer GP hyperparameters and assign them physical meaning, such as the QPO frequency. We also perform model selection between QPOs and alternative models such as red noise and show that this can be used to reliably find QPOs. This method is easily applicable to a variety of different astrophysical data sets. We demonstrate the use of this method on a range of short transients: a gamma-ray burst, a magnetar flare, a magnetar giant flare, and simulated solar flare data.

Accounting for stellar activity signals in radial-velocity data by using change point detection techniques

Context.Active regions on the photosphere of a star have been the major obstacle for detecting Earth-like exoplanets using the radial velocity (RV) method. A commonly employed solution for addressing stellar activity is to assume a linear relationship between the RV observations and the activity indicators along the entire time series, and then remove the estimated contribution of activity from the variation in RV data (overall correction method). However, since active regions evolve on the photosphere over time, correlations between the RV observations and the activity indicators will correspondingly be anisotropic.Aims.We present an approach that recognizes the RV locations where the correlations between the RV and the activity indicators significantly change in order to better account for variations in RV caused by stellar activity.Methods.The proposed approach uses a general family of statistical breakpoint methods, often referred to as change point detection (CPD) algorithms; several implementations of which are available in R and python. A thorough comparison is made between the breakpoint-based approach and the overall correction method. To ensure wide representativity, we use measurements from real stars that have different levels of stellar activity and whose spectra have different signal-to-noise ratios.Results.When the corrections for stellar activity are applied separately to each temporal segment identified by the breakpoint method, the corresponding residuals in the RV time series are typically much smaller than those obtained by the overall correction method. Consequently, the generalized Lomb–Scargle periodogram contains a smaller number of peaks caused by active regions. The CPD algorithm is particularly effective when focusing on active stars with long time series, such asαCen B. In that case, we demonstrate that the breakpoint method improves the detection limit of exoplanets by 74% on average with respect to the overall correction method.Conclusions.CPD algorithms provide a useful statistical framework for estimating the presence of change points in a time series. Since the process underlying the RV measurements generates anisotropic data by its intrinsic properties, it is natural to use CPD to obtain cleaner signals from RV data. We anticipate that the improved exoplanet detection limit may lead to a widespread adoption of such an approach. Our test on the HD 192310 planetary system is encouraging, as we confirm the presence of the two hosted exoplanets and we determine orbital parameters consistent with the literature, also providing much more precise estimates for HD 192310 c.

Improvement of Distance Measurement Based on Dispersive Interferometry Using Femtosecond Optical Frequency Comb.

Since the dispersive interferometry (DPI) based on optical frequency combs (OFCs) was proposed, it has been widely used in absolute distance measurements with long-distance and high precision. However, it has a serious problem for the traditional DPI based on the mode-locked OFC. The error of measurements caused by using the fast Fourier transform (FFT) algorithm to process signals cannot be overcome, which is due to the non-uniform sampling intervals in the frequency domain of spectrometers. Therefore, in this paper, we propose a new mathematical model with a simple form of OFC to simulate and analyze various properties of the OFC and the principle of DPI. Moreover, we carry out an experimental verification, in which we adopt the Lomb–Scargle algorithm to improve the accuracy of measurements of DPI. The results show that the Lomb–Scargle algorithm can effectively reduce the error caused by the resolution, and the error of absolute distance measurement is less than 12 μm in the distance of 70 m based on the mode-locked OFC.

Periodic Variations of Solar Corona Index during 1939–2020

Periodic behaviors of solar magnetic indicators might provide a clue for the understanding of solar dynamic processes. Combining with a Lomb–Scargle periodogram, the concentration of frequency and time via a multitapered synchrosqueezed transform is applied to investigate the periodic variations of modified coronal index for the time interval from 1 January 1939 to 31 August 2020. The main results are as follows: (1) During solar cycles 19 to 23, the Schwabe cycle of the modified coronal index is operating with its length variating between 10.5 and 11-yr, and the average value of length is 10.67-yr with standard deviation of 0.14-yr. (2) The Rieger-type periods are mainly distributed in a range from 120 to 200 days. In addition, the periods vary somewhat intermittently during cycles 18 to 24, which are operating with the highest power in cycles 21 and 22 while the power is much lower in cycles 23 and 24. (3) For rotation periods, the temporal variation exhibits a highly intermittent pattern as an asymmetrical distribution with its 25th, 50th, and 75th quantile of 26, 27.8, and 31-day, respectively. (4) Other mid-range periods are also detected with an average period length of 8.07, 5.44, 3.42, 2.3, and 1.01-yr.

The refinement of reprocessed GNSS three-decade displacement trajectory model with spectral analysis and hypothesis test

Extensive data collection, unified and rigorous data processing, and accurate construction of station motion model (especially the correction of co-seismic/post-seismic effects of large earthquakes) are three basic elements for the accuracy and reliability of Global Navigation Satellite System (GNSS) velocity. Thus, we take advantage of the sensitivity features of the spectral analysis and hypothesis test to refine the site movement trajectory model, and apply it to the reprocessed GNSS three-decade coordinate time series. Firstly, we reprocess GNSS observations and seismic records based on the updated convention and processing settings of International GNSS Service (IGS) repro3. Secondly, we use the Improved Lomb–Scargle Periodogram (ILSP) model to analyze the periodic characteristics of GNSS vertical time series. The results represent that the primary period of about 35% of sites is 365 days, and the secondary period of 20% of sites is 182 days. Thirdly, we evaluate the performance of different time series model component combination of the time series (a: velocity only; b: velocity + offset; c: velocity + offset + PSD; d: velocity + offset + PSD + period) and Post-Seismic Deformation (PSD) modes (PSD1: None; PSD 2: Exp; PSD 3: Log; PSD 4: Exp + Log). Fourthly, we use the chi-square test to assess the overall correctness of the trajectory model, followed by the t-test to test the significance of each parameter further, and then use the optimized model to refit and reanalyze GNSS time series. The analysis of the velocity results illustrates that the fitting accuracy of GNSS time series is 3–6 mm in the horizontal direction and 4–9 mm in the vertical direction. Lastly, we obtain a refined global three-dimensional velocity field based on GNSS three-decade time series, with the median velocity of Root Mean Square Error (RMSE) as 0.17, 0.17, and 0.32 mm/a in N/E/U direction. Compared with ITRF2014, the velocity difference is at 1–2 mm/a level due to differences in GNSS observations, trajectory model, and geodetic technology.

An investigation of the magnetic activity of HD 134319 based on TESS photometry and ground-based spectroscopy

ABSTRACT We present an analysis of the starspot properties and chromospheric activity on HD 134319 using high-precision photometry by Transiting Exoplanet Survey Satellite (TESS) in sectors 14–16 (T1) and 21–23 (T2) and high-resolution spectroscopy by the ELODIE spectrograph on 1.93-m telescope of Observatoire de Haute-Provence (OHP/ELODIE) and the High Resolution Echelle Spectrometer on Keck 10-m telescope of W. M. Keck Observatory (Keck/HIRES) during the years 1995–2013. We applied a two-spot model with generalized Lomb–Scargle (GLS) periodogram determined period of P = 4.436391 ± 0.00137 d to model chunks sliding over TESS light curve. We also measured the relative equivalent widths of Ca ii H and K, Hβ and Hα emissions by subtracting the overall spectrum from individual spectra. It was found that a two-spot configuration, namely a primary, slowly evolving and long-lasting spot (P) plus a secondary, rapidly evolving spot (S), was capable of explaining the data, although the actual starspot distribution cannot be derived from the collected data. Despite the spot radius–latitude degeneracy revealed in the best-fitting solutions, a sudden alternation between P and S radii followed by a gradual decrease of S in T1 and a decrease of both P and S from T1 to T2 were significant, corresponding to the evolution of magnetic activity. In addition, S revealed rotation and an oscillatory longitude migration synchronized to P in T1, but had a much larger migration than P in T2. This might indicate the evolution of the internal magnetic configuration. Chromospheric activity indicators were found to be tightly correlated with each other and revealed rotational modulation as well as a long-term decrease of emissions, implying the existence and evolution of magnetic activity on HD 134319.

Quasiperiodic Behavior in the γ-Ray Light Curve of the Blazar PKS 0405-385

We analyze the quasiperiodic oscillation (QPO) of the historical light curve of flat-spectrum radio quasars PKS 0405-385 detected by the Fermi Large Area Telescope from 2008 August to 2021 November. To identify and determine the QPO signal of PKS 0405-385 in the γ-ray light curve, we use four time series analysis techniques based on frequency and time domains, i.e., the Lomb–Scargle periodogram (LSP), the weighted wavelet z-transform (WWZ), the REDFIT, and the epoch folding. The results show that PKS 0405-385 has a quasiperiodic behavior of ∼2.8 yr with the significance of ∼4.3σ in Fermi long-term monitoring. Remarkably, we also performed QPO analysis in the G-band light curve observed from 2014 October to 2021 October using LSP and WWZ technology, and the results (∼4σ of significance) are consistent with the periodic detection in γ-ray. This may imply that the optical emission is radiated by an electron population in the same way as the γ-ray emission. In discussing the possible mechanism of quasiperiodic behavior, either the helical motion within a jet or the supermassive black hole binary system provides a viable explanation for the QPO of 2.8 yr, and the relevant parameters have been estimated.

Unusual Enhancement of Midlatitude Sporadic-E Layers in Response to a Minor Geomagnetic Storm

This study investigates the variations of middle and low latitude sporadic-E (Es) layers in response to a geomagnetic storm. Es layers are observed by five ionosondes located in the Eastern Asian sector. The critical frequencies of Es layers (foEs) at six stations increased in sequence from high latitude stations to low latitude stations after IMF/Bz turning southward. Lomb–Scargle analysis shows the amplification of semidiurnal oscillation amplitude in the vertical height of Es layers during geomagnetic disturbance. Modeling results of the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) show the enhancement of the wind field in the mesosphere and the lower thermosphere (MLT) region. Our study provides evidence that the enhanced wind field in the MLT region during the storm period could result in the enhancement of Es layers at middle and low latitude.

An improved snow depth retrieval method with adaptive noise reduction for GPS/GLONASS/Galileo/BDS multi-frequency signals

The Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique is an effective method of monitoring snow depth. The detrended signal-to-noise ratio (dSNR) series is analyzed by a Lomb–Scargle periodogram (LSP) to extract the characteristic frequency, which can be converted to the snow depth. However, the dSNR data are greatly affected by noise in the observation environment, which leads to an abnormal characteristic frequency and low accuracy of snow depth retrieval. In order to reduce the influence of noise and to ensure the correct extraction of the characteristic frequency, we present an improved adaptive retrieval method for the multi-constellation retrieval scenario. First, the dSNR sequences are decomposed adaptively into several singular spectrum components (SSCs) with different frequency scales by singular spectrum decomposition. Then, the corresponding SSCs are selected, according to the empirical scope of snow depth, to reconstruct the ‘pure’ dSNR series. Finally, the reconstructed signals are analyzed by LSP to derive the characteristic frequency, in order to obtain the snow depth. Multi-GNSS observations of site SG27 and site P351 from the plate boundary observation network in a representative period from winter 2019 to spring 2020 were used to validate the proposed method. The snow depths were estimated from individual signals, individual constellations and multi-GNSS combination using both the traditional and improved methods. The experimental results show that compared with the traditional method, the snow depth trend of the improved method is more consistent with the measured snow depth trend, especially in the early stage of snowfall. Furthermore, the proposed method shows a universal applicability to various signals of GPS, GLONASS, Galileo and BDS and the retrieval accuracy of all signals is improved to different degrees. When using multi-GNSS combination signals, the mean bias and root mean square error (RMSE) of multi-GNSS snow depth retrieval at site SG27 are improved from 4.6 and 6.2 cm to 4.2 and 5.4 cm, respectively. The mean bias and RMSE at site P351 are improved from 10.5 and 12.4 cm to 9.5 and 11.5 cm, respectively.

Quasi-periodic Oscillation Analysis for the BL Lacertae Object 1823+568

We studied the optical band periodic variability of 1823+568 using the Jurkevich method, the Lomb–Scargle periodogram and the REDFIT38 software, and found evidence of quasi-periodic oscillation. An unprecedented variability with period days was identified by three different analysis methods. This quasi-periodic variability most likely results from nonballistic helical jet motion driven by the orbital motion in a binary black hole system. Considering the light-travel time effect, the real physical period is P d = 67.1 yr. Moreover, we estimated that the primary black hole mass is M ≃ 1.92 × 109 M ⊙ to 3.43 × 109 M ⊙.

The Use of Caregivers' Smartphones to Assist Infants' Circadian Sleep-Wake Cycles.

Parents and caregivers lack knowledge regarding young children's sleep routines due to an absence of general guidelines about sleep development, and this knowledge gap has been associated with infants' sleep problems. Approximately 30% of infants develop sleep problems, including difficulty with falling asleep and night-waking. In this study, we sought to develop a new indicator of regularity in infants' circadian sleep-wake patterns. Our participants were healthy Japanese mothers and their infants (n = 172 infants; Mage = 4.9, SD = 3.5months). Mothers used their smartphones to record the time when their infants fell asleep and woke up in their natural home environments over 7days. We conducted least-squares spectrum analysis, a time-series analysis often used in chronobiology, to calculate the percentage variance (PVA) of the best-fitted cosine waves with a 24-hr periodicity in the infants' sleep records. We found that the PVA of the 24-hr cycles in the infants' sleep records were significantly correlated with the infants' age in months (r = 0.554, p < 0.001), variations in their waking-up (r = -0.316, p < 0.001) and falling asleep times (r = -0.430, p < 0.001), and sleep duration (r = -0.343, p < 0.001). Apart from these normative data, which are of potential comparative use by other investigators, we showed in this study that PVA data can be collected by infants' parents and caretakers through smartphones to provide parents an indicator of the regularity of an infant's 24-hr periodicity.

A Comparative Analysis to Deal with Missing Spectral Information Caused by RFI in Cosmological H i 21 cm Observations

We investigate the effect of radio-frequency interference (RFI) excision in estimating the cosmological H i 21 cm power spectrum. Flagging of RFI-contaminated channels results in a nonuniform sampling of the instrumental bandpass response. Hence, the Fourier transformation of visibilities from frequency to delay domain contaminates the higher foreground-free delay modes, and separating the spectrally fluctuating H i signal from spectrally smooth foregrounds becomes challenging. We have done a comparative analysis between two algorithms, one-dimensional CLEAN and least-squares spectral analysis (LSSA), which have been used widely to solve this issue in the literature. We test these algorithms using the simulated SKA-1 Low observations in the presence of different RFI flagging scenarios. We find that, in the presence of random flagging of data, both algorithms perform well and can mitigate the foreground leakage issue. But CLEAN fails to restrict the foreground leakage in the presence of periodic and periodic plus broadband RFI flagging and gives an extra bias to the estimated power spectrum. However, LSSA can restrict the foreground leakage for these RFI flagging scenarios and gives an unbiased estimate of the H i 21 cm power spectrum. We have also applied these algorithms to observations with the upgraded GMRT and found that both CLEAN and LSSA give consistent results in the presence of realistic random flagging scenarios for this observed data set. This comparative analysis demonstrates the effectiveness and robustness of these two algorithms in estimating the H i 21 cm power spectrum from data sets affected by different RFI scenarios.

A Possible 3 yr Quasi-periodic Oscillation in γ-Ray Emission from the FSRQ S5 1044+71

Variability is a typical observation feature of Fermi blazars, which sometimes shows quasi-periodic oscillation (QPO). In this work, we obtain 5 day binned light curves (with a time coverage of ∼12.9 yr) for S5 1044+71, based on Fermi-LAT data; apply five different methods—Date-compensated Discrete Fourier Transform, Jurkevich, Lomb–Scargle Periodogram, a Fortran 90 program, and the Weighted Wavelet Z-transform—to the γ-ray light curve; and find a possible QPO of 3.06 ± 0.43 yr at the significance level of ∼3.6σ. A binary black hole model, including an accretion model and a dual-jet model, is used to explain this quasi-periodic variability. We also estimate the Doppler factors and the apparent velocity for the two jet components. We speculate that this γ-ray quasi-periodic modulation suggests the presence of a binary supermassive black hole in S5 1044+71.

An automated radiotelemetry system (ARTS) for monitoring small mammals

Abstract The study of animals in nature is essential for developing an ecologically valid understanding of behaviour. Small mammals, however, are often fossorial and exceedingly difficult to monitor in the wild. This limits both the taxonomic scope of field observation, and excludes species that are powerful models for the study of behavioural mechanisms. Here, we implement an automated radiotelemetry system (ARTS) designed to track small fossorial mammals. Our ARTS uses an isotropic antenna array coupled with broadband receivers. We characterized transmission at our study site and tested the ARTS’s ability to track 48 prairie voles. We compared position estimates from nonlinear least squares, nonparametric and Bayesian trilateration methods and found Bayesian trilateration to have the smallest error. To examine the ability of the system to track biologically significant behaviour, we used ARTS data to investigate circadian rhythms of freely behaving prairie voles. We used Lomb–Scargle analysis to estimate periodic patterns from irregularly sampled time series. Prairie voles demonstrated circadian and ultradian movement. This ARTS offers a new tool to observe rodent behaviour at time‐scales and in environments that have not been previously possible, such as investigating social and spatial behaviours on the scale of minutes, hours and days in natural environments.

Five Decades of Chromospheric Activity in 59 Sun-like Stars and New Maunder Minimum Candidate HD 166620

Abstract We present five decades of chromospheric activity measurements in 59 Sun-like stars as time series. These include and extend the 35 yr of stellar chromospheric activity observations by the Mount Wilson Survey (1966–2001), and continued observations at Keck by the California Planet Search (1996–). The Mount Wilson Survey was studied closely in 1995, and revealed periodic activity cycles similar to the Sun’s 11 yr cycle. The California Planet Search provides more than five decades of measurements, significantly improving our understanding of these stars’ activity behavior. We have curated the activity measurements in order to create contiguous time series, and have classified the stellar sample according to a predetermined system. We have analyzed 29 stars with periodic cycles using the Lomb–Scargle periodogram, and present best-fit sinusoids to their activity time series. We report the best-fit periods for each cycling star, along with stellar parameters (T eff, log(g), vsin(i), etc.) for the entire sample. As a first application of these data, we offer a possible Maunder minimum candidate, HD 166620.