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It turns out optimal transport is easy! The "Spectral EMD" lets you compute optimal transport quickly and exactly in closed form -- incredibly useful for QCD and collider physics!
arxiv.org/abs/2410.05379
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Rikab Gambhir
181 posts
Rikab Gambhir
@Cornkab
Theoretical Physicist (Allegedly) | MIT CTP P.h.D. Student | don't sleep through dreams that can't come true
Cambridge, MA Katılım Aralık 2014
317 Takip Edilen612 Takipçiler
Rikab Gambhir retweetledi
In a new work with @bqp_equals_bpp, we parallelize quantum signal processing!
arxiv.org/abs/2409.19043
Our parallel QSP algorithm is tailored to property estimation, and distributes the computation over multiple independent quantum devices.
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Rikab Gambhir retweetledi
Can classical randomness accelerate quantum algorithms? Indeed, through randomized compiling!
arxiv.org/abs/2409.03744
We introduce stochastic quantum signal processing (QSP) as a randomly-compiled version of QSP, and reduce the cost of QSP-based algorithms by a factor of 1/2.
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Rikab Gambhir retweetledi
Great article about #MachineLearning in #ParticlePhysics Theory:
symmetrymagazine.org/article/machin…
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Rikab Gambhir retweetledi
New #paper on #arXiv today!
"Unifying Simulation and Inference with Normalizing Flows" with Haoxing Du, Vinicius Mikuni, Benjamin Nachman (@BPNachman), Ian Pang, and David Shih
arxiv.org/abs/2404.18992
(perfect timing for #EuCAIFCon24 this week :-) )
1/6
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Rikab Gambhir retweetledi
#CMSPaper 1286 studies whether, very rarely, top quarks decay without intermediate W bosons, specifically top to 2 other quarks and 1 charged lepton. It sets the world's strongest constraints, improving our knowledge by three to six orders of magnitude 💪 buff.ly/3xBgfwU
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Turns out you actually can get a job studying quantum color and shapes!
arxiv.org/abs/2302.12266
😡fermion, PhD@angryfermion
STEM major: what are you learning in school? kindergartener: colors and shapes STEM major: lmao good luck getting a job with that
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Rikab Gambhir retweetledi
#CMSPaper 1280 measures the strength of the strong nuclear force from the internal sub-blobs inside jets, the spray of particle debris that quarks and gluons leave when they are created. Yes, jets can measure one of the fundamental physics constants! buff.ly/49wJRsI
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Rikab Gambhir retweetledi
Rikab Gambhir retweetledi
#CMSPaper 1279 looks for new undiscovered particles decaying to a b quark and a Higgs boson, a b quark and a Z boson, or a t quark and a W boson. These quark-like objects are common in predictions where more Higgs bosons exist. It is a #null result. buff.ly/49BCTm8
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Rikab Gambhir retweetledi
An accelerator known as a muon collider could revolutionize particle physics—if it can be built.
Read that story and more this week in Science: scim.ag/6or
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Rikab Gambhir retweetledi
Just wrapped up a fun @AspenPhysics talk on "Machine Learning at Future Colliders" indico.cern.ch/event/1305841/… based on arxiv.org/abs/2309.06782 w/ @JoosepPata, Farouk Mokhtar, Mengke Zhang, @ericwulff, David Southwick, @MariaGirone4, @a3d3institute
GIF
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Give me a Moment to talk about ML for jet tagging:
"Moments of Clarity", a generalization of Deep Sets networks!
arxiv.org/abs/2403.08854
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Rikab Gambhir retweetledi
🎉🎉Out now: OmniJet-α: The first cross-task foundation model for particle physics (2403.05618)
Transfer from generative pre-training to supervised classification improves data efficiency by 2-3 orders of magnitude!
Thanks to hard work by @joschka_birk & AnnaH @quunihh @UHHMIN
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Cool paper I happened to find on arXiv randomly!
"Seeing Double" 👀 with @BPNachman
arxiv.org/abs/2402.14067
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Rikab Gambhir retweetledi
A recent passion project of mine has been to communicate a research result through an animated video, in an intuitive and pedagogical format. I’m happy to finally share this video, in which I discuss our recent work on neural-network quantum field states:
youtu.be/rrvZDZMii-0
YouTube
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We choose to go to the muon [...] not because it is easy but because it is hard
Muon Collider@MuonCollider
THIS. IS. OUR. MUON. SHOT!
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Rikab Gambhir retweetledi
Rikab Gambhir retweetledi
Sorry for silence recently, busy hosting #ML4Jets in Hamburg.
Thanks for all the seriously excellent developments on AI applied to particle physics (& beyond)
Not going to summarize the 133 (!) contributions here, but you can check out the slides:
indico.cern.ch/event/1253794
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