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14 results for “phase curve”
GJ 1214b MIRI phase curve analysis
<p>Outputs of the fiducial Gj 1214b analysis. Files:</p> <p>result.txt: eclipse depth, transit depth, and nightside Fp/Fs per wavelength bin. This file also reports amplitude and phase offset, but these are calculated ONLY from the first-order component of the phase curve, ignoring the second-order component. See amplitudes_and_phases.txt for the (relative) amplitude and phase offset while taking the second-order component into account.</p> <p>lightcurves.txt: best fit spectroscopic light curves</p> <p>Generate plots.ipynb: a Jupyter notebook that generates the *.png plots in the folder. If you're confused about the format of the data files, consult this notebook.</p> <p>*.png files: generated by the aforementioned Jupyter notebook. If you're confused about what a plot is showing, consult the notebook.</p> <p>white_lightcurve.txt: best fit white light curve</p> <p>white_envelope.txt, white_envelope_3sigma.txt: 1 sigma and 3 sigma envelopes of the white light curve</p> <p>white_light_result.txt: system parameters inferred from white light curve</p> <p>white_chain.npy: the emcee chain for the white light curve. Parameters: delta_t_transit, delta_t_eclipse, Fp, C1, D1, C2, D2, rp/rs, a/Rs, b, error_factor, Fstar, Aramp, tau, cy, slope.</p> <p>white_lnprobs.npy: ln(posterior) for every sample of the white chain</p> <p>chain_6000_6500.npy: the chain for the spectroscopic light curve spanning 6000--6500 Angstroms. Parameters: Fp, C1, D1, C2, D2, error_factor, rp/rs, Fstar, Aramp, tau, cy, slope</p> <p>lnprobs_6000_6500.npy: ln(posterior) for the spectroscopic chain mentioned above</p> <p>amplitudes_and_phases.txt: relative amplitude, (max - min) / max, of the phase curve, along with the phase offset, defined as the position of the phase curve maximum relative to mid-eclipse. Negative means east.</p> <p>calc_amplitude_offset.py: script that calculates the amplitudes and phase offsets in the above file, starting from the spectroscopic chain. Usage: python calc_amplitude_offset.py 6000, for the bin 6000-6500 Angstrom.</p> <p>fiducial_stellar_spectrum.fits: the stellar spectrum we adopted</p> <p>data.pkl: the reduced data that we fit for with emcee</p> <p>positions.txt: x and y positions inferred for the trace</p>
WACCM Test File for the Variable Star Phase Curve Package
<p>This is a Whole Atmosphere Community Climate Model (WACCM) dataset that is used to test WACCM integration for the Variable Star Phase Curve (VSPEC) code.</p>
Supplementary Information: Exoplanet atmosphere retrievals in 3D using phase curve data with ARCiS: application to WASP-43b. Chubb and Min, A&A (2022).
<p>Supplementary information containing additional figures of the journal article 'Exoplanet atmosphere retrievals in 3D using phase curve data with ARCiS: application to WASP-43b' by K. L. Chubb and M. Min, published in Astronomy & Astrophysics (2022).</p>
Diagram of apparent resistivity phase curves of magnetotelluric in Songliao Basin, Northeast China
<p>The research area is located at an expanse of 120,000 square kilometers in northeastern China, including Heilongjiang Province, Jilin Province, and Liaoning Province (about 123°-127° east longitude and about 45°-49° north latitude). The basin is divided into five primary structural units according to the distribution and development characteristics of the fault depressions, namely; the central depression zone , the southeast uplift zone , the northeast uplift zone ,the northern plunge zone , and the west slope zone . Multiple secondary fault depressions and fault uplifts lie inside. This work used a total of 157 broadband magnetotelluric sounding data points. MTU-5 magnetotelluric instruments produced by Phoenix Geophysics of Canada were used for field collection of magnetotelluric sounds and the effective frequency band was 320~0.0005 Hz. The poles were arranged according to the tensor measurement method. Each measuring point measures 5 components, 3 of them being magnetic field components while the other 2 are mutually orthogonal horizontal electric field components. The signal acquisition time was about 20 hours and the average point distance was 10 km. This is a diagram of apparent resistivity phase curves including every broadband magnetotelluric sounding data points.</p>
Reproduction package for Spectroscopically resolved partial phase curve of the rapid heating and cooling of the highly-eccentric Hot Jupiter HAT-P-2b with WFC3
<p>This is a basic reproduction package for the paper "<span>Spectroscopically resolved partial phase curve of the rapid heating and cooling of the highly-eccentric Hot Jupiter </span><span>HAT-P-2b with WFC3</span>"</p> <p>by [Jacobs, B.; Désert, J. -M.; Lewis, N. et al. (2024)]</p> <p>Abstract:</p> <p><span>The extreme environments of transiting close-in exoplanets in highly-eccentric orbits serve as ideal labo</span><span>ratories for testing exo-atmospheric physics. Spectroscopically resolved phase curves not only allow for the </span><span>characterization of their thermal response to irradiation changes but also unveil phase-dependent atmospheric </span><span>chemistry and dynamics.</span></p> <p><span>We observed a partial phase curve of the highly-eccentric close-in giant planet HAT-P-2b (</span><span>e</span> <span>=</span> <span>0</span><span>.</span><span>51023)</span><br><span>with the Wide Field Camera 3 (WFC3) aboard the</span> <span>Hubble Space Telescope</span><span>.</span> <span>Using these data, we update </span><span>the planet’s orbital parameters and radius, and we retrieve high-frequency pulsations consistent with those re</span><span>ported in Spitzer data. We find that the peak in planetary flux occurs at 6</span><span>.</span><span>7</span> <span>±</span> <span>0</span><span>.</span><span>6 hr after periastron, with a </span><span>heating timescale of 9</span><span>.</span><span>0</span><span>+</span><span>3</span><span>.</span><span>5</span><br><span>−</span><span>2</span><span>.</span><span>1</span> <span>hr, and a cooling timescale of 3</span><span>.</span><span>6</span><span>+</span><span>0</span><span>.</span><span>7</span><span>−</span><span>0</span><span>.</span><span>6</span> <span>hr. We compare the light-curve to a suite of</span><br><span>1-dimensional and 3-dimensional forward models, varying the planet’s chemical composition. The strong con</span><span>trast in flux increase and decrease timescales before and after periapse indicates an opacity term that emerges </span><span>during the planet’s heating phase. We suggest that more emerging H</span><span>−</span> <span>than expected from chemical equilibrium </span><span>models could be the reason for the mismatch between models and the data.</span></p> <p><span>We used a common-mode based method that does not assume a functional form to extract phase-resolved </span><span>spectra. The analysis of these spectra is challenging because of the unknown accuracy of the spectral slope and </span><span>absolute flux levels. The phase-resolved spectra are largely featureless, possibly indicating an inhomogeneous </span><span>dayside.</span> <span>However, we identified an anomalously high flux in the spectroscopic bin that coincides with the </span><span>hydrogen Paschen</span> <span>β</span> <span>line and that is potentially connected to the planet’s orbit.</span> <span>We exclude an instrumental </span><span>origin and we discuss several alternative, astrophysical origins.</span></p>
Products for "An absolute mass, precise age, and hints of planetary winds for WASP-121 A and b from a JWST NIRSpec phase curve"
<p>The repository contains radial velocity data for WASP-121b from Sing, Evans-Soma, Rustamkulov, Lothringer, Mayne, & Schlaufman from the paper titled "An absolute mass, precise age, and hints of planetary winds for WASP-121 A and b from a JWST NIRSpec phase curve" (2024, AAS jounals). The record contains two data files corresponding to JWST/NIRSpec radial velocity data as shown in Figures 6 (NRS2) and 7 (NRS1). Each file contains five collumns, normalized time (BJD_TDB-2400000.5) in days, orbital phase, the planet radial velocity (km/s) and the 1-sigma uncertainties in the radial velocity (km/s).</p>
Relative Phase Data to 'Experimental observation of curved light-cones in a quantum field simulator', arXiv:2209.09132
<p><strong>Relative phase profiles and averaged density profiles for the results shown in arXiv:2209.09132</strong></p> <p>Each file "phase_and_mean_density_scan_X.mat" contains data for a measurement presented in the manuscript, where "X" is the corresponding scan number.<br> The following table shows the relevant scan number to measurement descriptions mentioned in the manuscript (see Table S1 in the SI Appendix).</p> <table align="center"> <thead> <tr> <th scope="col">Measurement description</th> <th scope="col">Scan number</th> </tr> </thead> <tbody> <tr> <td> <p> Homogeneous (main text)</p> </td> <td> 9185</td> </tr> <tr> <td> <p> Inhomogeneous with sharp edges </p> </td> <td> 10419</td> </tr> <tr> <td> <p> Inhomogeneous with smoothed edges</p> </td> <td> 8935</td> </tr> <tr> <td> <p> Homogeneous 2 (SI Appendix)</p> </td> <td> 10455</td> </tr> </tbody> </table> <p> </p> <p><strong>File Contents</strong></p> <p>Each file contains the following variables:</p> <ul> <li>"phase": A MATLAB cell containing all the phase profiles for every time step. Thus, "phase{t_ind}" is a matrix where rows represent experimental realizations and columns the spatial grid points. For example, "phase{5}(1,:)" would be a one-dimensional phase profile, representing the first realization of the fifth time step. To learn more about the extraction of phase profiles, read Section 2 and see Fig. S5 in SI Appendix.</li> <li>"z_grid_phase_si": Vector. Grid points for phase profiles in SI units (m).</li> <li>"averaged_density_si": Vector. Averaged initial linear density in SI units (m^-1). See Fig. 1(a).</li> <li>"z_grid_density_si": Vector. Grid points for averaged density in SI units (m).</li> <li>"times_si": Vector. Time points in SI units (s).</li> </ul> <p> </p> <p><strong>Matlab script calculating the velocity field</strong></p> <p>In addition to the data, a MATLAB script (velocity_field_calculation.m) loads a data file and calculates the velocity field and its correlations following the equations in the manuscript:</p> <ul> <li>"u": MATLAB cell. Velocity field for every time step.</li> <li>"u_u_corr": MATLAB cell. Second-order correlations of the velocity field for every time step.</li> <li>"std_u_u_corr": MATLAB cell. Standard deviation of second-order correlations of the velocity field for every time-step.</li> </ul> <p>Finally, the script plots "u_u_corr" for all the time steps and plots the averaged linear density.</p>
Antibiotic phase transition curves
<p>Phase transitions are an important and extensively studied concept in physics. The insights derived from understanding phase transitions in physics have also recently and successfully been applied to a number of different phenomena in biological systems. Here, we provide a brief review of phase transitions and their role in explaining biological processes ranging from collective behavior in animal flocks to neuronal firing. We also highlight a new and exciting area where phase transition theory is particularly applicable: population collapse and extinction. We discuss how phase transition theory can give insight into a range of extinction events such as population decline due to climate change or microbial responses to environmental stressors such as antibiotic treatment.</p>
Antibiotic phase transition curves
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Isotropic phase velocity dispersion curves for Superior Province.
<p>SuperiorProvince-DispCurves is a composite dataset of dispersion curves and their associated uncertainties extracted from three Rayleigh wave tomographic studies Darbsyhire et al., 2013, Petrescu et al., 2017, and Foster et al., 2020. We took a weighted average of phase velocities in regions where these different datasets overlapped, with a higher weighting for the dataset with the densest ray path coverage in order to reduce edge effects. It includes a README file.</p>
Data from: Evaluation of the phase-dependent rhythm control of human walking using phase response curves
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CSRM Level 2 dataset: event-station Rayleigh wave phase and group velocity dispersion curves in continental China from regional earthquake data
<p>This dataset contains the <strong>54,792</strong> event-station Rayleigh wave phase and group velocity dispersion curves from vertical-component waveforms of <strong>226 </strong>regional earthquakes recorded by <strong>1463</strong> seismic stations. This dataset results from a project of constructing the high-resolution China Seismological Reference Model (<strong>CSRM-1.0</strong>) in the top 100 km of the crust and uppermost mantle in continental China (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">model link</a>). </p> <p>本数据库包含了利用中国大陆区域 <strong>1463</strong> 个地震台站记录的 <strong>226</strong> 个区域地震的波形数据计算的 <strong>54,792 </strong>条事件-台站间瑞利波相/群速度频散曲线。该数据库源于构建中国大陆区域高精度地壳和上地幔顶部 100 公里三维地震学模型(<strong>CSRM-1.0</strong>)的工作 (<a href="https://doi.org/10.1029/2024JB029520">Xiao et al, JGR, 2024</a>) (<a href="https://doi.org/10.5281/zenodo.11098135">模型链接</a>) 。</p> <p>If you face any problem or issue in the usage of this dataset, please feel free to communicate with the corresponding author Xiao Xiao (<strong>xiaox.seis@gmail.com</strong>). </p>
Melting curve and phase relations of Fe-Ni alloys at high pressure and high temperature: implications for the Earth core composition
<p>X-ray absorption data supporting results of the manuscript:</p> <p>Melting curve and phase relations of Fe-Ni alloys at high pressure and high temperature: implications for the Earth core composition</p> <p>submitted to Geophysical Research Letters</p> <p> </p>
Energy-volume curves and and structures for TCP phases in the Co-Ti-W system
<p>Numeric data from the DFT calculated energy - volume curves for intermetalic compounds in the Co-Ti-W system, including TCP phases. Data is arranged as a json file with a structure that implies a unique identifier for each compound and includes e-v curves, crystal structure for the equilibrium volume, and results from the Birch-Murnaghan fit.</p> <p>Data relatad to https://doi.org/10.1016/j.actamat.2017.07.037</p>
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