iiinova — where your digital self keeps evolving

Reposted by Nihar Gupte

Annalena Kofler @annalenakofler.bsky.social · 02/07/2026

What a crazy week! I was selected to attend the 75th Lindau Nobel Laureate Meeting and had the opportunity to present my work in front of Nobel Laureates. That was scary, but they are amazing people and loved to chat. #LINO75

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Nihar Gupte @nihar-gupte.bsky.social · 29/04/2026

Hi everyone I wanted to show a couple features of my website. Firstly, a page which shows evolutions of the binary black holes we have detected with @ligo.org @egovirgo.bsky.social @kagra. Click the link to learn more! nihargupte.com/blog/catalog... #blackholes

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Nihar Gupte @nihar-gupte.bsky.social · 01/01/2026

I have been reading Weinberg's "Quantum Theory of Fields", it is an excellent book and rejuvenating my interest in physics. Well, I guess thats my new years resolution, at least make it to chapter 5 👾

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Nihar Gupte @nihar-gupte.bsky.social · 03/12/2025

Often we talk about accuracy and speed of inference during ML applications to science. However, an equally important feature is flexibility. This is because real data requires flexibility (changing settings during inference time). Please check out Annalena’s thread for more info!

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Annalena Kofler @annalenakofler.bsky.social · 03/12/2025

1/ 🌀 New paper alert! We introduce Dingo-T1, a flexible transformer-based deep learning model for gravitational-wave (GW) data analysis. It adapts to different detector & frequency settings, improving inference efficiency and flexibility 🚀 #AI #MachineLearning #Physics #Astronomy #AcademicSky

Scientific poster with dark background and two black holes illustrated in the center. The paper visualizes gravitational waves, and explains how parameter estimation is performed with DINGO. The standard DINGO model and the DINGO-T1 architectures are illustrated and results are shown. For example, it is possible to reanalyze the same event with different detector configurations with DINGO-T1, illustrated bz a corner plot.

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Olly Long @hyperbolly.bsky.social · 16/11/2025

How much information can we gain by pushing numerical relativity to its limit by simulating black hole scattering encounters? My latest paper (below) explores these extreme regions of the black-hole scattering parameter space using simulations generated using the Spectral Einstein Code (SpEC).

arxiv.org

Black-hole scattering with numerical relativity: Self-force extraction and post-Minkowskian validation

The asymptotic nature of unbound binary-black-hole encounters provides a clean method for comparing different approaches for modeling the two-body problem in general relativity. In this work, we use n...

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Christopher Berry @cplberry.bsky.social · 12/11/2025

Oo! Interesting #GravitationalWave candidate #S251112cm potentially from a *subsolar* mass source If real, the source is probably has chirp mass ~0.1–0.87 solar masses False alarm rate 1 in 6.2 yr GraceDB gracedb.ligo.org/superevents/... GCN gcn.nasa.gov/circulars/42... Rating 📏🍬 [🧪🔭⚛️]

Initial sky localization. 90% area 1,200 sq deg.

Initial three-dimensional volume localization. Distance around 96 Mpc.

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Nihar Gupte @nihar-gupte.bsky.social · 20/10/2025

Great set of talks/panels today by Kip Thorne, Thibault Damour, Zvi Bern, Dennis Lehmkuhl, Leor Barack, Luc Blanchet, Gerhard Schäfer, and Clifford Will about the history of the two body problem. At the MPI for Grav. Phys. in Potsdam.

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Phil Lynch @physlynch.bsky.social · 12/09/2025

New paper on the arXiv today about systematic errors when modelling the gravitation waveform from extreme mass ratio inspirals and their impact on LISA data science Huge thanks to my collaborators, especially Hassan Khalvati, for getting this project over the line! 🧪⚛️🔭🧮 arxiv.org/abs/2509.08875

A posting on the arXiv preprint server.

Title: Systematic errors in fast relativistic waveforms for Extreme Mass Ratio Inspirals

Authors: Hassan Khalvati, Philip Lynch, Ollie Burke, Lorenzo Speri, Maarten van de Meent, Zachary Nasipak

Abstract: Accurate modeling of Extreme Mass-Ratio Inspirals (EMRIs) is essential for extracting reliable information from future space-based gravitational wave observatories. Fast waveform generation frameworks adopt an offline/online architecture, where expensive relativistic computations (e.g. self-force and black hole perturbation theory) are performed offline, and waveforms are generated rapidly online via interpolation across a multidimensional parameter space. In this work, we investigate potential sources of error that result in systematic bias in these relativistic waveform models, focusing on radiation-reaction fluxes. Two key sources of systematics are identified: (i) the intrinsic inaccuracy of the flux data, for which we focus on the truncation of the multipolar mode sum, and (ii) interpolation errors from transitioning to the online stage. We quantify the impact of mode-sum truncation and analyze interpolation errors by using various grid structures and interpolation schemes. For circular orbits in Kerr spacetime with spins larger than a≥0.9, we find that ℓmax≥30 is required for the necessary accuracy. We also develop an efficient Chebyshev interpolation scheme, achieving the desired accuracy level with significantly fewer grid points compared to spline-based methods. For circular orbits in Kerr spacetimes, we demonstrate via Bayesian studies that interpolating the flux to a maximum global relative error that is equal to the small mass ratio is sufficient for parameter estimation purposes. For 4-year long quasi-circular EMRI signals with SNRs=O(100) and mass-ratios 10^−4−10^−6, a global relative error of 10−6 yields mismatches <10^−3 and negligible parameter estimation biases.

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Carl Rodriguez @carlrodriguez.bsky.social · 26/08/2025

Ok, there's a lot of cool stuff in the new @ligo.org collaboration paper (and I'll let the actual LVK members talk about most of it), but one very cool thing from the populations paper (arxiv.org/abs/2508.18083) that jumps out to me is this plot of the effective spin for 30-40 solar mass BHs: 🔭🧪

top panel of figure 13 from the LVK populations paper (linked in post)

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Nihar Gupte @nihar-gupte.bsky.social · 26/08/2025

Everyone is saying it looks like a phoenix I feel like it looks more like a butterfly or a moth from a top down view The beak of the phoenix/antenna of the moth is the heaviest one we've seen so far, and by a good bit!

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Nihar Gupte @nihar-gupte.bsky.social · 17/07/2025

An interesting talk today at #gramaldi #amaldi16 by Gautam Satishchandran on how black holes cause decoherence of quantum experiments. The research is a thought experiment but also provides estimates on the decoherence time as a function of the distance between the experiment and the black hole.

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Nihar Gupte @nihar-gupte.bsky.social · 17/07/2025

My favorite slide of the day from #gramaldi #amaldi16. Isobel Romero-Shaw talks about how we can use spin distributions and eccentricities to differentiate between field triples, isolated binary evolution and dynamical formation. It was a cool artwork as well

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Nihar Gupte @nihar-gupte.bsky.social · 15/07/2025

My favorite slide today from Oliver Jennrich at #gramaldi #amaldi16. It shows how rich gravitational waves from extreme mass ratio inspirals are for testing general relativity

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LIGO Scientific Collaboration @ligo.org · 14/07/2025

We are excited to announce the discovery of #GW231123, a gravitational-wave signal from the merger of two high-mass black holes to form one about 190–265 times the mass of our Sun ligo.org/ligo-virgo-k... #O4IsHere 🔭🧪☄️

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Nihar Gupte @nihar-gupte.bsky.social · 05/06/2025

Trump has decided he wants to kill one of humanity's most sensitive instruments for understanding the universe for... about the cost of... half a fighter jet (or less). Source: www.nasa.gov/wp-content/u...

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SXS Collaboration @sxs-collaboration.bsky.social · 20/05/2025

We are excited to release a major update to our catalog of binary black hole simulations, available at arxiv.org/abs/2505.13378! Such simulations are key to LIGO/Virgo/KAGRA being able to extract science from their gravitational wave detections. 1/13 🧪⚛️🔭

Figure 1 from our new catalog paper. We accurately capture precession, memory, eccentricity, and high mass ratio systems. For full details, see the paper.

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Christopher Berry @cplberry.bsky.social · 01/05/2025

For those with an artistic streak, #GR24Amaldi16 will be hosting an art science exhibition. We welcome submissions inspired by the themes of the meeting (gravity, cosmology, black holes, gravitational waves, astrophysics). Anyone can submit! uofgravity.github.io/amaldi-art/ 🧪🔭🐚

uofgravity.github.io

Amaldi Art Show

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Nihar Gupte @nihar-gupte.bsky.social · 22/03/2025

Wanted to shout out this paper: by @maximiliandax.bsky.social and @stephenrgreen.bsky.social. It allows us to perform parameter inference of binary neutron stars in a second. These binary neutron stars are measured with gravitational waves! Here’s a poster I made for the LVK meeting in Barcelona!

Poster showing neutron stars and the remnant kilonova. It also shows the posterior distribution of the neutron star parameters.

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Claire Lamman @clairelamman.bsky.social · 20/03/2025

...so is it time to throw a funeral for LCDM? That depends on who you ask 😂. It's certainly a sign that DESI's DR1 results were not a statistical fluke. Even if LCDM prevails, SOMETHING is weird and that's a great sign that we're learning something new.

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Nihar Gupte @nihar-gupte.bsky.social · 24/02/2025

GOAT meets GOAT to create the GOAT of Astro YouTube series

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Annalena Kofler @annalenakofler.bsky.social · 14/01/2025

1/ 🌌 New Paper Alert: How can we decode the atmospheres of exoplanets efficiently and reliably? The latest work by my amazing collaborator @timothygebhard.bsky.social introduces Flow Matching Posterior Estimation for atmospheric retrieval. 🚀🧵👇 #AI #MachineLearning #Physics #Astronomy #AcademicSky

Scientific poster with the title "Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets adaptive noise levels". The background is dark with a blue exoplanet in the center and the surface of a yellow star at the bottom.

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Nihar Gupte @nihar-gupte.bsky.social · 12/01/2025

I had the opportunity to answer questions at the Royal Astronomical Society (@royalastrosoc.bsky.social) about GWs+ML. Thanks to all the organizers from Royal Holloway (esp. Ann and Mattia) for inviting me! I was able to work on this fountain pen sketch of the Victoria statue before the workshop:

A blue pen sketch of queen Victoria’s statue in front of Buckingham palace.

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Nihar Gupte @nihar-gupte.bsky.social · 08/01/2025

Woke up this morning to see the sad news of the Palisades and Eaton fires. I hope everyone, their families, and pets are ok. I can't imagine what kind of anxiety it is wondering if your home is ok or not :( Here's some info on the fires based on a project I was working on in 2019. 1/11

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Nihar Gupte @nihar-gupte.bsky.social · 15/12/2024

I visited #Tokyo, #Kyoto, #Osaka, #Nara and Mt. #Fuji for ~2 weeks. #Japan, is a cool place with amazing people! I do travel sketchbooking so I thought I would share my sketches. Usually, they’re scribbled at the sites in awkward positions, but the sketches feel way more organic that way.

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Nihar Gupte @nihar-gupte.bsky.social · 13/12/2024

I want to compliment the way scientists are portrayed in the Netflix series #Arcane. They're portrayed as people *first* and scientists *second*. This leads to organic motivations and character development.

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Annalena Kofler @annalenakofler.bsky.social · 02/12/2024

1/ 🚀 New Paper Alert: Spotlight at NeurIPS ML and the Physical Sciences Workshop! We explore the intersection of high-energy physics and machine learning. What's the challenge we’re targeting, and why does it matter? Let's dive in! 🧵👇 🚀 #AI #MachineLearning #Physics #ML4PS #NeurIPS #AcademicSky

Scientific poster with dark-blue background. Title: Flow Annealed Importance Sampling Bootstrap meets differentiable particle physics. The poster contains multiple sections: Generation of data in particle physics, normalizing flows, training approaches, and results for a 2D distribution (lambda_c^+ decay) and a 8D distribution (top production). Additionally, results for the efficiency over the number of target evaluations are shown.

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Michael Puerrer @michaelpuerrer.bsky.social · 23/11/2024

I'm co-organizing a workshop on Scientific Machine Learning for Gravitational Wave Astronomy at ICERM, Providence, RI, June 2 - 6, 2025. Applications are now open at icerm.brown.edu/program/topi...! We recommend applying by December 15, 2024.

Image credit: Max Planck Institute for Gravitational Physics, Simulating eXtreme Spacetimes Collaboration and Airborne Hydro Mapping GmbH

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Stephen Green @stephenrgreen.bsky.social · 04/11/2024

🚀 I'm hiring--two postdocs and a research software engineer (RSE) to work with me on gravitational waves and machine learning at Nottingham! The posts are funded by my UKRI Future Leaders Fellowship. Postdocs: jobs.nottingham.ac.uk/vacancy.aspx... RSE: jobs.nottingham.ac.uk/vacancy.aspx...

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Nihar Gupte @nihar-gupte.bsky.social · 22/11/2024

Now that I’m here let show off my poster! In this paper we found evidence for eccentricity in Binary Black holes observed by LIGO-Virgo-KAGRA. You can read the paper here: arxiv.org/abs/2404.14286 and my Twitter summary here: x.com/nihar_gupte/...

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Nihar Gupte @nihar-gupte.bsky.social · 22/11/2024

Downloaded this app because I saw that you can control what you see from the algorithm. I was seeing way too much garbage on my timeline on Twitter and wanted to see more science and art. Hopefully it can happen!

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