Results 1351-1400 of 2121 (2090 ASCL, 31 submitted)
Phantom-GRAPE is a numerical software library to accelerate collisionless $N$-body simulation with SIMD instruction set on x86 architecture. The Newton's forces and also central forces with an arbitrary shape f(r), which have a finite cutoff radius r_cut (i.e. f(r)=0 at r>r_cut), can be quickly computed.
Phantom is a smoothed particle hydrodynamics and magnetohydrodynamics code focused on stellar, galactic, planetary, and high energy astrophysics. It is modular, and handles sink particles, self-gravity, two fluid and one fluid dust, ISM chemistry and cooling, physical viscosity, non-ideal MHD, and more. Its modular structure makes it easy to add new physics to the code.
phase_space_cosmo_fisher produces Fisher matrix 2D contours from which the constraints on cosmological parameters can be derived. Given a specified redshift array and cosmological case, 2D marginalized contours of cosmological parameters are generated; the code can also plot the derivatives used in the Fisher matrix. In addition, this package can generate 3D plots of qH^2 and other cosmological quantities as a function of redshift and cosmology.
PhAst (Photometry-Astrometry) is an IDL astronomical image viewer based on the existing application ATV which displays and analyzes FITS images. It can calibrate raw images, provide astrometric solutions, and do circular aperture photometry. PhAst allows the user to load, process, and blink any number of images. Analysis packages include image calibration, photometry, and astrometry (provided through an interface with SExtractor, SCAMP, and missFITS). PhAst has been designed to generate reports for Minor Planet Center reporting.
PHOEBE (PHysics Of Eclipsing BinariEs) is a modeling package for eclipsing binary stars, built on top of the widely used WD program (Wilson & Devinney 1971). This introductory paper overviews most important scientific extensions (incorporating observational spectra of eclipsing binaries into the solution-seeking process, extracting individual temperatures from observed color indices, main-sequence constraining and proper treatment of the reddening), numerical innovations (suggested improvements to WD's Differential Corrections method, the new Nelder & Mead's downhill Simplex method) and technical aspects (back-end scripter structure, graphical user interface). While PHOEBE retains 100% WD compatibility, its add-ons are a powerful way to enhance WD by encompassing even more physics and solution reliability.
PHOENIX is a general-purpose state-of-the-art stellar and planetary atmosphere code. It can calculate atmospheres and spectra of stars all across the HR-diagram including main sequence stars, giants, white dwarfs, stars with winds, TTauri stars, novae, supernovae, brown dwarfs and extrasolar giant planets.
The Photon Simulator (PhoSim) is a set of fast photon Monte Carlo codes used to calculate the physics of the atmosphere, telescope, and detector by using modern numerical techniques applied to comprehensive physical models. PhoSim generates images by collecting photons into pixels. The code takes the description of what astronomical objects are in the sky at a particular time (the instance catalog) as well as the description of the observing configuration (the operational parameters) and produces a realistic data stream of images that are similar to what a real telescope would produce. PhoSim was developed for large aperture wide field optical telescopes, such as the planned design of LSST. The initial version of the simulator also targeted the LSST telescope and camera design, but the code has since been broadened to include existing telescopes of a related nature. The atmospheric model, in particular, includes physical approximations that are limited to this general context.
Photo-z-SQL is a flexible template-based photometric redshift estimation framework that can be seamlessly integrated into a SQL database (or DB) server and executed on demand in SQL. The DB integration eliminates the need to move large photometric datasets outside a database for redshift estimation, and uses the computational capabilities of DB hardware. Photo-z-SQL performs both maximum likelihood and Bayesian estimation and handles inputs of variable photometric filter sets and corresponding broad-band magnitudes.
Photodynam facilitates so-called "photometric-dynamical" modeling. This model is quite simple and this is reflected in the code base. A N-body code provides coordinates and the photometric code produces light curves based on coordinates.
PHOTOM performs photometry of digitized images. It has two basic modes of operation: using an interactive display to specify the positions for the measurements, or obtaining those positions from a file. In both modes of operation PHOTOM performs photometry using either the traditional aperture method or via optimal extraction. When using the traditional aperture extraction method the target aperture can be circular or elliptical and its size and shape can be varied interactively on the display, or by entering values from the keyboard. Both methods allow the background sky level to be either sampled interactively by the manual positioning of an aperture, or automatically from an annulus surrounding the target object. PHOTOM is the photometry backend for the GAIA tool (ascl:1403.024) and is part of the Starlink software collection (ascl:1110.012).
PHOTOMETRYPIPELINE (PP) provides calibrated photometry from imaging data obtained with small to medium-sized observatories. PP uses Source Extractor (ascl:1010.064) and SCAMP (ascl:1010.063) to register the image data and perform aperture photometry. Calibration is obtained through matching of field stars with reliable photometric catalogs. PP has been specifically designed for the measurement of asteroid photometry, but can also be used to obtain photometry of fixed sources.
Photon makes simple 1D plots in python. It uses mainly matplotlib and PyQt5 and has been build to be fully customizable, allowing the user to change the fontstyle, fontsize, fontcolors, linewidth of the axes, thickness, and other parameters, and see the changes directly in the plot. Once a customization is created, it can be saved in a configuration file and reloaded for future use, allowing reuse of the customization for other plots. The main tool is a graphical user interface and it is started using a command line interface.
PhotoRApToR (PHOTOmetric Research APplication TO Redshifts) solves regression and classification problems and is specialized for photo-z estimation. PhotoRApToR offers data table manipulation capabilities and 2D and 3D graphics tools for data visualization; it also provides a statistical report for both classification and regression experiments. The code is written in Java; the machine learning model is in C++ to increase the core execution speed.
Photutils provides tools for detecting and performing photometry of astronomical sources. It can estimate the background and background rms in astronomical images, detect sources in astronomical images, estimate morphological parameters of those sources (e.g., centroid and shape parameters), and perform aperture and PSF photometry. Written in Python, it is an affiliated package of Astropy (ascl:1304.002).
PHOX is a novel, virtual X-ray observatory designed to obtain synthetic observations from hydro-numerical simulations. The code is a photon simulator and can be apply to simulate galaxy clusters. In fact, X-ray observations of clusters of galaxies continue to provide us with an increasingly detailed picture of their structure and of the underlying physical phenomena governing the gaseous component, which dominates their baryonic content. Therefore, it is fundamental to find the most direct and faithful way to compare such observational data with hydrodynamical simulations of cluster-like objects, which can currently include various complex physical processes. Here, we present and analyse synthetic Suzaku observations of two cluster-size haloes obtained by processing with PHOX the hydrodynamical simulation of the large-scale, filament-like region in which they reside. Taking advantage of the simulated data, we test the results inferred from the X-ray analysis of the mock observations against the underlying, known solution. Remarkably, we are able to recover the theoretical temperature distribution of the two haloes by means of the multi-temperature fitting of the synthetic spectra. Moreover, the shapes of the reconstructed distributions allow us to trace the different thermal structure that distinguishes the dynamical state of the two haloes.
ISOPHOT is one of the instruments on board the Infrared Space Observatory (ISO). ISOPHOT Interactive Analysis (PIA) is a scientific and calibration interactive data analysis tool for ISOPHOT data reduction. Written in IDL under Xwindows, PIA offers a full context sensitive graphical interface for retrieving, accessing and analyzing ISOPHOT data. It is available in two nearly identical versions; a general observers version omits the calibration sequences.
PIAO is an efficient memory-controlled Python code that uses the standard spherical overdensity (SO) algorithm to identify halos. PIAO employs two additional parameters besides the overdensity Δc. The first is the mesh-box size, which splits the whole simulation box into smaller ones then analyzes them one-by-one, thereby overcoming a possible memory limitation problem that can occur when dealing with high-resolution, large-volume simulations. The second is the smoothed particle hydrodynamics (SPH) neighbors number, which is used for the SPH density calculation.
PICASO (Planetary Intensity Code for Atmospheric Scattering Observations), written in Python, computes the reflected light of exoplanets at any phase geometry using direct and diffuse scattering phase functions and Raman scattering spectral features.
Piccard is a Bayesian-inference pipeline for Pulsar Timing Array (PTA) data and interacts with Tempo2 (ascl:1210.015) through libstempo. The code is used mainly for single-pulsar analysis and gravitational-wave detection purposes of full Pulsar Timing Array datasets. Modeling of the data can include correlated signals per frequency or modeled spectrum, with uniform, dipolar, quadrupolar, or anisotropic correlations; multiple error bars and EFACs per pulsar; and white and red noise. Timing models can be numerically included, either by using the design matrix (linear timing model), or by calling libstempo for the full non-linear timing model. Many types of samplers are included. For common-mode mitigation, the signals can be reconstructed mitigating arbitrary signals simultaneously.
Pico is an algorithm that quickly computes the CMB scalar, tensor and lensed power spectra, the matter transfer function and the WMAP 5 year likelihood. It is intended to accelerate parameter estimation codes; Pico can compute the CMB power spectrum and matter transfer function, as well as any computationally expensive likelihoods, in a few milliseconds. It is extremely fast and accurate over a large volume of parameter space and its accuracy can be improved by using a larger training set. More generally, Pico allows using massively parallel computing resources, including distributed computing projects such as Cosmology@Home, to speed up the slow steps in inherently sequential calculations.
PICsar simulates the magnetosphere of an aligned axisymmetric pulsar and can be used to simulate other arbitrary electromagnetics problems in axisymmetry. Written in Fortran, this special relativistic, electromagnetic, charge conservative particle in cell code features stretchable body-fitted coordinates that follow the surface of a sphere, simplifying the application of boundary conditions in the case of the aligned pulsar; a radiation absorbing outer boundary, which allows a steady state to be set up dynamically and maintained indefinitely from transient initial conditions; and algorithms for injection of charged particles into the simulation domain. PICsar is parallelized using MPI and has been used on research problems with ~1000 CPUs.
pieflag compares bandpass-calibrated data to a clean reference channel and identifies and flags essentially all bad data. pieflag compares visibility amplitudes in each frequency channel to a 'reference' channel that is rfi-free (or manually ensured to be rfi-free). pieflag performs this comparison independently for each correlation on each baseline, but will flag all correlations if threshold conditions are met. To operate effectively, pieflag must be supplied with bandpass-calibrated data. pieflag has two core modes of operation (static and dynamic flagging) with an additional extend mode; the type of data largely determines which mode to choose. Instructions for pre-processing data and selecting the mode of operation are provided in the help file. Once pre-processing and selecting the mode of operation are done, pieflag should work well 'out of the box' with its default parameters.
The pile-up gnuplot script generates a Monte Carlo simulation with a selectable number of randomized drawings (1000 by default, ~1min on a modern laptop). For each realization, the script calculates the torque acting on a hot Jupiter around a young, solar-type star as a function of the star-planet distance. The total torque on the planet is composed of the disk torque in the type II migration regime (that is, the planet is assumed to have opened up a gap in the disk) and of the stellar tidal torque. The model has four free parameters, which are drawn from a normal or lognormal distribution: (1) the disk's gas surface density at 1 astronomical unit, (2) the magnitude of tidal dissipation within the star, (3) the disk's alpha viscosity parameter, and (4) and the mean molecular weight of the gas in the disk midplane. For each realization, the total torque is screened for a distance at which it becomes zero. If present, then this distance would represent a tidal migration barrier to the planet. In other words, the planet would stop migrating. This location is added to a histogram on top of the main torque-over-distance panel and the realization is counted as one case that contributes to the overall survival rate of hot Jupiters. Finally, the script generates an output file (PDF by default) and prints the hot Jupiter survival rate for the assumed parameterization of the star-planet-disk system.
PINGSoft2 visualizes, manipulates and analyzes integral field spectroscopy (IFS) data based on either 3D cubes or Raw Stacked Spectra (RSS) format. Any IFS data can be adapted to work with PINGSoft2, regardless of the original data format and the size/shape of the spaxel. Written in IDL, PINGSoft2 is optimized for fast visualization rendering; it also includes various routines useful for generic astronomy and spectroscopy tasks.
Morphological classification is one of the most demanding challenges in astronomy. With the advent of all-sky surveys, an enormous amount of imaging data is publicly available, and are typically analyzed by experts or encouraged amateur volunteers. For upcoming surveys with billions of objects, however, such an approach is not feasible anymore. PINK (Parallelized rotation and flipping INvariant Kohonen maps) is a simple yet effective variant of a rotation-invariant self-organizing map that is suitable for many analysis tasks in astronomy. The code reduces the computational complexity via modern GPUs and applies the resulting framework to galaxy data for morphological analysis.
PINOCCHIO generates catalogues of cosmological dark matter halos with known mass, position, velocity and merger history. It is able to reproduce, with very good accuracy, the hierarchical formation of dark matter halos from a realization of an initial (linear) density perturbation field, given on a 3D grid. Its setup is similar to that of a conventional N-body simulation, but it is based on the powerful Lagrangian Perturbation Theory. It runs in just a small fraction of the computing time taken by an equivalent N-body simulation, producing promptly the merging histories of all halos in the catalog.
PINT (PINT Is Not Tempo3) analyzes high-precision pulsar timing data, enabling interactive data analysis and providing an extensible and flexible development platform for timing applications. PINT utilizes well-debugged public Python packages and modern software development practices (e.g., the NumPy and Astropy libraries, version control and development with git and GitHub, and various types of testing) for increased development efficiency and enhanced stability. PINT has been developed and implemented completely independently from traditional pulsar timing software such as TEMPO (ascl:1509.002) and Tempo2 (ascl:1210.015) and is a robust tool for cross-checking timing analyses and simulating data.
PINTofALE was originally developed to analyze spectroscopic data from optically-thin coronal plasmas, though much of the software is sufficiently general to be of use in a much wider range of astrophysical data analyses. It is based on a modular set of IDL tools that interact with an atomic database and with observational data. The tools are designed to allow easy identification of spectral features, measure line fluxes, and carry out detailed modeling. The basic philosophy of the package is to provide access to the innards of atomic line databases, and to have flexible tools to interactively compare with the observed data. It is motivated by the large amount of book-keeping, computation and iterative interaction that is required between the researcher and observational and theoretical data in order to derive astrophysical results. The tools link together transparently and automatically the processes of spectral "browsing", feature identification, measurement, and computation and derivation of results. Unlike standard modeling and fitting engines currently in use, PINTofALE opens up the "black box" of atomic data required for UV/X-ray analyses and allows the user full control over the data that are used in any given analysis.
Pippi (parse it, plot it) operates on MCMC chains and related lists of samples from a function or distribution, and can merge, parse, and plot sample ensembles ('chains') either in terms of the likelihood/fitness function directly, or as implied posterior probability densities. Pippi is compatible with ASCII text and hdf5 chains, operates out of core, and can post-process chains on the fly.
PISA (Position, Intensity and Shape Analysis) routines deal with the location and parameterization of objects on an image frame. The core of this package is the routine PISAFIND which performs image analysis on a 2-dimensional data frame. The program searches the data array for objects that have a minimum number of connected pixels above a given threshold and extracts the image parameters (position, intensity, shape) for each object. The image parameters can be determined using thresholding techniques or an analytical stellar profile can be used to fit the objects. In crowded regions deblending of overlapping sources can be performed. PISA is distributed as part of the Starlink software collection (ascl:1110.012).
We introduce and implement two novel ideas for modeling lensed quasars. The first is to require different lenses to agree about H0. This means that some models for one lens can be ruled out by data on a different lens. We explain using two worked examples. One example models 1115+080 and 1608+656 (time-delay quadruple systems) and 1933+503 (a prospective time-delay system) all together, yielding time-delay predictions for the third lens and a 90% confidence estimate of H0-1=14.6+9.4-1.7 Gyr (H0=67+9-26 km s-1 Mpc-1) assuming ΩM=0.3 and ΩΛ=0.7. The other example models the time-delay doubles 1520+530, 1600+434, 1830-211, and 2149-275, which gives H0-1=14.5+3.3-1.5 Gyr (H0=67+8-13 km s-1 Mpc-1). Our second idea is to write the modeling software as a highly interactive Java applet, which can be used both for coarse-grained results inside a browser and for fine-grained results on a workstation. Several obstacles come up in trying to implement a numerically intensive method thus, but we overcome them.
PkdGRAV2 is a high performance N-body treecode for self-gravitating astrophysical simulations. It is designed to run efficiently in serial and on a wide variety of parallel computers including both shared memory and message passing architectures. It can spatially adapt to large ranges in particle densities, and temporally adapt to large ranges in dynamical timescales. The code uses a non-standard data structure for efficiently calculating the gravitational forces, a variant on the k-D tree, and a novel method for treating periodic boundary conditions.
Pkdgrav3 is an 𝒪(N) gravity calculation method; it uses a binary tree algorithm with fifth order fast multipole expansion of the gravitational potential, using cell-cell interactions. Periodic boundaries conditions require very little data movement and allow a high degree of parallelism; the code includes GPU acceleration for all force calculations, leading to a significant speed-up with respect to previous versions (ascl:1305.005). Pkdgrav3 also has a sophisticated time-stepping criterion based on an estimation of the local dynamical time.
PLAN (PLanetesimal ANalyzer) identifies and characterizes planetesimals produced in numerical simulations of the Streaming Instability that includes particle self-gravity with code Athena (ascl:1010.014). PLAN works with the 3D particle output of Athena and finds gravitationally bound clumps robustly and efficiently. PLAN — written in C++ with OpenMP/MPI — is massively parallelized, memory-efficient, and scalable to analyze billions of particles and multiple snapshots simultaneously. The approach of PLAN is based on the dark matter halo finder HOP (ascl:1102.019), but with many customizations for planetesimal formation. PLAN can be easily adapted to analyze other object formation simulations that use Lagrangian particles (e.g., Athena++ simulations). PLAN is also equipped with a toolkit to analyze the grid-based hydro data (VTK dumps of primitive variables) from Athena, which requires the Boost MultiDimensional Array Library.
The Planck simulation package takes a cosmological model specified by the user and calculates a potential CMB sky consistent with this model, including astrophysical foregrounds, and then performs a simulated observation of this sky. This Simulation embraces many instrumental effects such as beam convolution and noise. Alternatively, the package can simulate the observation of a provided sky model, generated by another program such as the Planck Sky Model software. The Planck simulation package does not only provide Planck-like data, it can also be easily adopted to mimic the properties of other existing and upcoming CMB experiments.
Given two planets P1 and P2 with arbitrary orbits, planetary3br calculates all possible semimajor axes that a third planet P0 can have in order for the system to be in a three body resonance; these are identified by the combination k0*P0 + k1*P1 + k2*P2. P1 and P2 are assumed to be not in an exact two-body resonance. The program also calculates three "strengths" of the resonance, one for each planet, which are only indicators of the dynamical relevance of the resonance on each planet. Sample input data are available along with the Fortran77 source code.
PlanetPack facilitates and standardizes the advanced analysis of radial velocity (RV) data for the goal of exoplanets detection, characterization, and basic dynamical N-body simulations. PlanetPack is a command-line interpreter that can run either in an interactive mode or in a batch mode of automatic script interpretation.
planetplanet models exoplanet transits, secondary eclipses, phase curves, and exomoons, as well as eclipsing binaries, circumbinary planets, and more. The code was originally developed to model planet-planet occultation (PPO) light curves for the TRAPPIST-1 system, but it is generally applicable to any exoplanet system. During a PPO, a planet occults (transits) the disk of another planet in the same planetary system, blocking its thermal (and reflected) light, which can be measured photometrically by a distant observer. planetplanet is coded in C and wrapped in a user-friendly Python interface.
PlasmaPy provides core functionality and a common framework for data visualization and analysis for plasma physics. It has modules for basic plasma physics calculations, running desktop-scale simulations to test preliminary ideas such as one-dimensional MHD/PIC or test particles, or comparing data from two different sources, such as simulations and spacecraft.
PLATO Simulator is an end-to-end simulation software tool designed for the performance of realistic simulations of the expected observations of the PLATO mission but easily adaptable to similar types of missions. It models and simulates photometric time-series of CCD images by including models of the CCD and its electronics, the telescope optics, the stellar field, the jitter movements of the spacecraft, and all important natural noise sources.
PLATON (PLanetary Atmospheric Transmission for Observer Noobs) calculates transmission spectra for exoplanets and retrieves atmospheric characteristics based on observed spectra; it is based on ExoTransmit (ascl:1611.005). PLATON supports the most common atmospheric parameters, such as temperature, metallicity, C/O ratio, cloud-top pressure, and scattering slope. It also has less commonly included features, such as a Mie scattering cloud model and unocculted starspot corrections.
Plonk analyzes and visualizes smoothed particle hydrodynamics simulation data. It is built on the scientific Python ecosystem, including NumPy, Matplotlib, Cython, h5py, SymPy, and pandas. Plock's visualization module uses Splash (ascl:1103.004) to produce images using smoothed particle hydrodynamics interpolation. The code is modular and extendible, and can be scripted or used interactively.
PLplot is a cross-platform software package for creating scientific plots. To help accomplish that task it is organized as a core C library, language bindings for that library, and device drivers which control how the plots are presented in non-interactive and interactive plotting contexts. The PLplot core library can be used to create standard x-y plots, semi-log plots, log-log plots, contour plots, 3D surface plots, mesh plots, bar charts and pie charts. Multiple graphs (of the same or different sizes) may be placed on a single page, and multiple pages are allowed for those device formats that support them. PLplot has core support for Unicode. This means for our many Unicode-aware devices that plots can be labelled using the enormous selection of Unicode mathematical symbols. A large subset of our Unicode-aware devices also support complex text layout (CTL) languages such as Arabic, Hebrew, and Indic and Indic-derived CTL scripts such as Devanagari, Thai, Lao, and Tibetan. PLplot device drivers support a number of different file formats for non-interactive plotting and a number of different platforms that are suitable for interactive plotting. It is easy to add new device drivers to PLplot by writing a small number of device dependent routines.
Plumix is a small package for generating mass segregated star clusters. Its output can be directly used as input initial conditions for NBODY4 or NBODY6 code. Mass segregation stands as one of the most robust features of the dynamical evolution of self-gravitating star clusters. We formulate parametrized models of mass segregated star clusters in virial equilibrium. To this purpose we introduce mean inter-particle potentials for statistically described unsegregated systems and suggest a single-parameter generalization of its form which gives a mass-segregated state. Plumix is a numerical C-code generating the cluster according the algorithm given for construction of appropriate star cluster models. Their stability over several crossing-times is verified by following the evolution by means of direct N-body integration.
PLUTO is a modular Godunov-type code intended mainly for astrophysical applications and high Mach number flows in multiple spatial dimensions. The code embeds different hydrodynamic modules and multiple algorithms to solve the equations describing Newtonian, relativistic, MHD, or relativistic MHD fluids in Cartesian or curvilinear coordinates. PLUTO is entirely written in the C programming language and can run on either single processor machines or large parallel clusters through the MPI library. A simple user-interface based on the Python scripting language is available to setup a physical problem in a quick and self-explanatory way. Computations may be carried on either static or adaptive (structured) grids, the latter functionality being provided through the Chombo adaptive mesh refinement library.
Particle-Mesh (PM) codes are still very useful tools for testing predictions of cosmological models in cases when extra high resolution is not very important. We release for public use a cosmological PM N-body code. The code is very fast and simple. We provide a complete package of routines needed to set initial conditions, to run the code, and to analyze the results. The package allows you to simulate models with numerous combinations of parameters: open/flat/closed background, with or without the cosmological constant, different values of the Hubble constant, with or without hot neutrinos, tilted or non-tilted initial spectra, different amount of baryons.
The parallel PM N-body code PMFAST is cost-effective and memory-efficient. PMFAST is based on a two-level mesh gravity solver where the gravitational forces are separated into long and short range components. The decomposition scheme minimizes communication costs and allows tolerance for slow networks. The code approaches optimality in several dimensions. The force computations are local and exploit highly optimized vendor FFT libraries. It features minimal memory overhead, with the particle positions and velocities being the main cost. The code features support for distributed and shared memory parallelization through the use of MPI and OpenMP, respectively.
The current release version uses two grid levels on a slab decomposition, with periodic boundary conditions for cosmological applications. Open boundary conditions could be added with little computational overhead. Timing information and results from a recent cosmological production run of the code using a 3712^3 mesh with 6.4 x 10^9 particles are available.
PMFASTIC is a parallel initial condition generator, a slab decomposition Fortran 90 parallel cosmological initial condition generator for use with PMFAST. Files required for generating initial dark matter particle distributions and instructions are included, however one would require CMBFAST to create alternative transfer functions.
pNbody is a parallelized python module toolbox designed to manipulate and interactively display very large N-body systems. It allows the user to perform complicated manipulations with only very few commands and to load an N-body system and explore it interactively using the python interpreter. pNbody may also be used in python scripts. pNbody contains graphical facilities for creating maps of physical values of the system, such as density, temperature, and velocities maps. Stereo capabilities are also implemented. pNbody is not limited by file format; the user may use a parameter file to redefine how to read a preferred format.
PANOPTES (Panoptic Astronomical Networked Observatories for a Public Transiting Exoplanets Survey) is a citizen science project for low cost, robotic detection of transiting exoplanets. POCS (PANOPTES Observatory Control System) is the main software driver for the PANOPTES telescope system, responsible for high-level control of the unit. POCS defines an Observatory class that automatically controls a commercially available equatorial mount, including image analysis and corresponding mount adjustment to obtain a percent-level photometric precision.
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