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gravitational-physicist
Expert-thinking profile for Gravitational Physicist (GW data analysis / matched-filter search & PE / numerical relativity / GR tests (LVK, GWOSC)): Reasons from calibrated strain, colored non-stationary noise PSDs, matched-filter SNR, and Bayesian posteriors through PyCBC/GstLAL/cWB searches, Bilby/LALInference PE with NRSur/SEOBNR/IMRPhenom waveforms, and …
make-your-photos-more-striking
This prompt instructs an image-generation model to create a cinematic, overhead portrait of a single stationary subject on a brick city sidewalk, styled with a moody 35mm film aesthetic. The outcome is a 4:3 image with shallow depth of field and sharp focus on the subject, while the surrounding crowd appears motion-blurred to emphasize contrast between stil…
model-markov-chain
Build and analyze discrete or continuous Markov chains including transition matrix construction, state classification, stationary distribution computation, and mean first passage times. Use when modeling a memoryless system with observed transition counts or rates, computing long-run steady-state probabilities, determining expected hitting times or absorpti…
model-markov-chain
Build and analyze discrete or continuous Markov chains including transition matrix construction, state classification, stationary distribution computation, and mean first passage times. Use when modeling a memoryless system with observed transition counts or rates, computing long-run steady-state probabilities, determining expected hitting times or absorpti…
model-markov-chain
Build and analyze discrete or continuous Markov chains including transition matrix construction, state classification, stationary distribution computation, and mean first passage times. Use when modeling a memoryless system with observed transition counts or rates, computing long-run steady-state probabilities, determining expected hitting times or absorpti…
model-markov-chain
Build and analyze discrete or continuous Markov chains including transition matrix construction, state classification, stationary distribution computation, and mean first passage times. Use when modeling a memoryless system with observed transition counts or rates, computing long-run steady-state probabilities, determining expected hitting times or absorpti…
model-markov-chain
Build and analyze discrete or continuous Markov chains including transition matrix construction, state classification, stationary distribution computation, and mean first passage times. Use when modeling a memoryless system with observed transition counts or rates, computing long-run steady-state probabilities, determining expected hitting times or absorpti…
model-markov-chain
Build and analyze discrete or continuous Markov chains including transition matrix construction, state classification, stationary distribution computation, and mean first passage times. Use when modeling a memoryless system with observed transition counts or rates, computing long-run steady-state probabilities, determining expected hitting times or absorpti…
model-markov-chain
Build and analyze discrete or continuous Markov chains including transition matrix construction, state classification, stationary distribution computation, and mean first passage times. Use when modeling a memoryless system with observed transition counts or rates, computing long-run steady-state probabilities, determining expected hitting times or absorpti…
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