Results for “radio-astronomy”

Guides authorized RF/SDR security research for signal identification, demodulation analysis, and replay feasibility studies in shielded lab environments.

Analyzes stellar structure, galactic dynamics, orbital mechanics, gravitational lensing, cosmic microwave background, and exoplanet detection methods.

Perform astronomical research and data analysis with coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time handling, and table operations.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Perform astronomical data analysis with Astropy: coordinate transformations, unit conversions, FITS I/O, cosmological calculations, time handling, table operations, and WCS transformations.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Provides guidance for using the Astropy Python library in astronomical research, covering coordinates, units, FITS files, cosmology, tables, time, and WCS transformations.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Provides guidance on using the Astropy library for astronomy and astrophysics workflows, including units, coordinates, FITS I/O, tables, time, WCS, and cosmology.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Perform astronomical research and data analysis with coordinate transformations, unit conversions, FITS file operations, cosmological calculations, time handling, and tabular data manipulation.

Performs astronomical data analysis with astropy: coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time handling, and table operations.

Set up and verify a connection to an NI USRP radio (USRP E320, N300, N310, N320, N321, X300, X310, or X410) using Wireless Testbench. Use when connecting a USRP for the first time, configuring radio hardware, troubleshooting connection failures, or verifying a radio setup. Covers host inspection (OS, NIC type/speed/MTU), device discovery (findsdru, probesdru), UHD version checking, programmatic radio configuration, and basebandTransceiver verification. Also use when the user mentions USRP setup, radio not found, connection errors, dropped samples, or network configuration for SDR hardware.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Performs astronomical data analysis with astropy: coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time systems, tables, and WCS.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Design, select, and analyze waveforms for radar, sonar, and active sensing using the Phased Array System Toolbox. Covers LFM, NLFM, FMCW, phase-coded, CW, stepped FM, custom IQ, ambiguity functions, sidelobe reduction, and Doppler tolerance. Key objects: phased.LinearFMWaveform, phased.NonlinearFMWaveform, phased.CustomFMWaveform, phased.PhaseCodedWaveform, phased.FMCWWaveform, phased.SteppedFMWaveform, phased.MFSKWaveform, phased.RectangularWaveform, nlfmspec2freq, shapespectrum, ambgfun, pambgfun, sidelobelevel, legendreseq, mlseq, radarWaveformGenerator.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Communications-domain literature review with Claude-style knowledge-base-first retrieval. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, related work, a survey, or a landscape summary. Search Zotero, Obsidian, and local paper folders first when available, then search IEEE Xplore, ScienceDirect, ACM Digital Library, and broader web in that order.

Computes mass-spectral similarity and identifies compounds for metabolomics with matchms — comparing mass spectra, scoring similarity (cosine, modified cosine), and searching spectral libraries to annotate unknowns. Use when matching MS/MS spectra, identifying metabolites, or library searching; for full LC-MS/MS proteomics pipelines use pyopenms. Part of the AlterLab Academic Skills suite.

Embody Carl Sagan's voice and perspective to communicate science with wonder, rigor, and accessibility.

Multi-format channel name parsing for KINTSUGI CHANNELNAMES.txt files

Detect structural macro regime transitions (1-2 year horizon) using cross-asset ratio analysis, analyzing RSP/SPY concentration, yield curve, credit conditions, size factor, equity-bond relationship, and sector rotation to identify regime shifts.

A radio button component for single selection from a set of options in Naive UI. Supports individual radio buttons, radio groups, and button-style radio groups with various sizes and states.