Tootfinder

I don't like pipes. I think this is idiomatic R:
mbhps |> select(mopfama) |> mutate(mopfama = ifelse(mopfama <0, NA, mopfama)) -> tabdat
To my old eyes that seems a weird way of writing nested functions, and this would be more sensible:
tabdat <- mutate(select(mbhps, mopfama), mopfama = ifelse(mopfama <0, NA, mopfama))
This dplyr-piping is what used to be called syntactic sugar. I think its purpose is to make code look more like a command languag…

🇺🇦 Auf radioeins läuft...
King Josephine:
🎵 Note To Self
#NowPlaying #KingJosephine
https://kingjosephine.bandcamp.com/album/note-to-self
https://open.spotify.com/track/5vgOPlBmpHfcYBCth3PWpK

Eikä kyllä muidenkaan, alle 10%..
Suomalaisten muovinkierrätys ei yllä EU:n tavoitteisiin https://www.ts.fi/uutiset/6736491
Less than 10% of global plastics manufactured from recycled materials, findings reveal

Suomalaisten muovinkierrätys ei yllä EU:n tavoitteisiin
Valtaosa suomalaisista kertoo lajittelevansa muovia ahkerasti, mutta vain noin 30 prosenttia muovipakkauksista päätyy kierrätykseen.

Simulation-based Inference of Massive Black Hole Binaries using Sequential Neural Likelihood
Iv\'an Mart\'in V\'ilchez, Carlos F. Sopuerta
https://arxiv.org/abs/2509.13842

Simulation-based Inference of Massive Black Hole Binaries using Sequential Neural Likelihood
We propose a machine learning-based approach for parameter estimation of Massive Black Hole Binaries (MBHBs), leveraging normalizing flows to approximate the likelihood function. By training these flows on simulated data, we can generate posterior samples via Markov Chain Monte Carlo with a relatively reduced computational cost. Our method enables iterative refinement of smaller models targeting specific MBHB events, with significantly fewer waveform template evaluations. However, dimensionalit…

🇺🇦 #NowPlaying on KEXP's #MorningShow
Weezer:
🎵 Say It Ain’t So
#Weezer
https://ffrevival.bandcamp.com/track/weezer-say-it-aint-so
https://open.spotify.com/track/56MEbUIvvfEEkLIl51wxGD

🇺🇦 #NowPlaying on #BBC6Music's #NickGrimshaw
Nirvana:
🎵 Love Buzz
#Nirvana
https://madmusicianmagician.bandcamp.com/track/nirvana-love-buzz-cover
https://open.spotify.com/track/5muVpPu8Fj9fXfDbbqDdrZ

🇺🇦 #NowPlaying on KEXP's #Early
Pearl Jam:
🎵 Daughter
#PearlJam
https://djaf.bandcamp.com/track/pearl-jam-daughter-edit-redrum
https://open.spotify.com/track/53eJFr4Mfbw5PXJ01K6cFw

Identifying massive black hole binaries via light curve variability in optical time-domain surveys
Alfredo Chiesa, David Izquierdo-Villalba, Alberto Sesana, Fabiola Cocchiararo, Alessia Franchini, Alessandro Lupi, Daniele Spinoso, Silvia Bonoli
https://arxiv.org/abs/2508.21510

Identifying massive black hole binaries via light curve variability in optical time-domain surveys
Accreting massive black hole binaries (MBHBs) often display periodic variations in their emitted radiation, providing a distinctive signature for their identification. In this work, we explore the MBHBs identification via optical variability studies by simulating the observations of the LSST survey. To this end, we generate a population of MBHBs using the L-Galaxies semi-analytical model, focusing on systems with observed orbital periods $\leq$ 5 years. This ensures that at least two complete c…

The Doppler boosted LISA response to gravitational waves
Tom van der Steen, Henri Inchausp\'e, Thomas Hertog, Aur\'elien Hees
https://arxiv.org/abs/2509.10038 https://…

The Doppler boosted LISA response to gravitational waves
The future space-based gravitational wave observatory LISA is expected to detect massive black hole binaries (MBHBs) with high signal-to-noise ratios (SNRs), ranging up to thousands. Such high-precision observations require accurate modeling of the detector response. However, current derivations of the response function neglect the motion of the spacecraft during light travel time, omitting velocity-dependent terms of order $β= v/c \sim 10^{-4}$. In this work, we derive the velocity-dependent …

🇺🇦 #NowPlaying on KEXP's #VarietyMix
freekind.:
🎵 Kind to Yourself
#freekind
https://legererecordings.bandcamp.com/track/kind-to-yourself
https://open.spotify.com/track/7MM0vIYBvAW1HSfsyFErKf