Lingxiao Wang

Deputy Team Director @riken_en, Assistant Professor @UTokyo_News_en, exploring strongly interacting matter with AI, working on machine learning physics.

[Emad @EMostaque]

If Claude is good enough for Nobel Prize winners it is good enough for you

https://t.co/P5pM4MGSqQ

[橋本幸士 Koji Hashimoto @hashimotostring]

記事で「生成科学」の名前を取り上げてくださっています．
楽しくやっていきますよ！
興味のある方はぜひご注目ください．
https://t.co/RKEzGZ7h0d

[橋本幸士 Koji Hashimoto @hashimotostring]

#学習物理学 領域は，中間評価としてA+の評価をいただきました．非常に活発な研究と，領域の多様な取り組みが高く評価されました．
皆さま，これからもどうぞよろしくお願いします．

文部科学省 令和7年度科学研究費助成事業（学術変革領域研究（A））に係る中間・事後評価について
https://t.co/KPHdwe0r7A

[Lingxiao Wang @lingxiao225]

We even ran proof-of-concept experiments on IBM Quantum hardware — showing quantum computers could shed light on social behavior. 🚀 #QuantumComputing #Sociophysics

[Lingxiao Wang @lingxiao225]

New (crazy) preprint out: “Quantum Simulations of Opinion Dynamics” explores how quantum superposition, entanglement, and measurement-induced collapse can model consensus formation, polarization, and collective decision-making. https://t.co/7TQn238LQP

[橋本幸士 Koji Hashimoto @hashimotostring]

ドイツ量子フェス！

https://t.co/qG1N6hHx63

ドイツにお住まいの皆さま、ドイツ量子フェスが11月15日にミュンスターで開催されます．

量子の講演や音楽会など，楽しみましょう！

チケットはこちらから→
https://t.co/qtOl1CQ2ZB

[Lingxiao Wang @lingxiao225]

Thrilled to start my new journey as an Assistant Professor(concurrent) at Institute for Physics of Intelligence in UTokyo! Exciting times ahead 🚀
https://t.co/WdWfYUe59f

[Institute for Advanced Study (IAS) @the_IAS]

The Institute remembers Chen Ning Yang, past Professor in the School of Mathematics/Natural Sciences, who died on October 18. At IAS, he produced a body of work which redefined how we conceptualize the fundamental forces and symmetries of the universe: https://t.co/nowev4yMCx

[Jürgen Schmidhuber @SchmidhuberAI]

More on CNN history: https://t.co/HdCanIaCCl Why did "modern" CNNs emerge in Japan 1979-1988 (Fukushima's 1979 CNN architecture → Zhang et al.'s 1988 backpropagation-trained CNN)? Let's look back at the 1980s. Back then, Japan was the envy of the world. Before the 1990 crash, the Tokyo stock market was the world's largest, and the world's 6 most valuable public companies were all Japanese. So were the world's richest business men. According to the real estate market, tiny Japan was 4 times more valuable than the much bigger US. The central square mile of Tokyo had the value of California. Japan had far more robots than any other country, and by far the most expensive AI project: the 5th Generation Project. Interestingly, this project had little to do with neural networks; it was mostly about logic programming and expert systems. So Fukushima and colleagues were outsiders back then. But at least there was sufficient funding in Japan, even for such unpopular types of blue skies research. Today, the rest of the world can be thankful for that. See also https://t.co/3Xfc5qoWQT

[Lingxiao Wang @lingxiao225]

もし、行き詰まりがまったくないとすれば、それは十分に難しい問題に挑戦していないからでしょう。

如果你从未陷入困境，那可能是因为你没有尝试解决一个足够困难的问题。

[Kengo Hirachi @kengohirachi]

多くの方に研究科長式辞を読んで頂いているようで嬉しいです。妻の感想は「帽子が似合っていない」。ポイントはそこではないと思う。 https://t.co/aMTWEmaMzH

[Lei Wang @wangleiphy]

Autoregressive model: alphabets, actions, and atoms https://t.co/UQvHvzcq0M This lecture tried to offer a unified perspective to LLM, RL, and atomistic modeling!

[a. li @luckypennyy]

AI-Empowered Astronomy for Open Science
https://t.co/ADrPdsUFG2
Live broadcast starting tomorrow >>>

[Satoshi Matsuoka @ProfMatsuoka]

Riken, including our center R-CCS, is hiring researchers big time, from PIs to postdocs to interns. We have the best support for international researches; in fact the % of non-JP researchers at R-CCS is approaching 50 % now. Come work with us! https://t.co/DhTYia461v

[Quantinuum @QuantinuumQC]

🥇Announcing the 1st commercial application for quantum computers!

Quantinuum, along with our partners JPMorganChase, @Argonne, @ORNL, and @UTAustin, have turned our quantum computer into a reliable and accessible source of high-quality randomness.

🔗https://t.co/cThUiu3Oc5

[Lingxiao Wang @lingxiao225]

@riken_en @RIKEN_JP Just got reported by iTHEMS news🥳 https://t.co/LhkoQiTsJj

[Lingxiao Wang @lingxiao225]

For those who have not yet subscribed, here is the download link, enjoy it !🥳
https://t.co/VqlUb1GAV8

[Lingxiao Wang @lingxiao225]

🚀 Excited to share our latest Perspective paper !
🔑 Key Insight: Physics-driven learning integrates domain-specific physics into ML, revolutionizing how we solve inverse problems in diverse physical sciences🤖🔬#PhysicsAI

[橋本幸士 Koji Hashimoto @hashimotostring]

AIの理論物理ベンチマーク．

[Masahito Yamazaki / 山崎雅人 @196884]

"The Quantum Frontier of Machine Learning," Kavli IPMU, March 11, 2025 https://t.co/UicUUiNmZ3

[Kyle Cranmer @KyleCranmer]

I’m pretty excited about our new paper, which is a follow up to our last paper using AI to help solve a problem in theoretical particle physics. (With Lance, @f_charton, Matthias, Tianji, and @merz_garrett

[Lingxiao Wang @lingxiao225]

@rothkopfAK We can only emphasize physics-driven designs for machine learning/deep learning. Regarding the works you mentioned, we fully acknowledge their significance. These topics are thoroughly discussed in our longer review in PPNP https://t.co/v3WW3alTTC

[Lingxiao Wang @lingxiao225]

🚀 Excited to share our latest Perspective paper !
🔑 Key Insight: Physics-driven learning integrates domain-specific physics into ML, revolutionizing how we solve inverse problems in diverse physical sciences🤖🔬#PhysicsAI

[Nature Reviews Physics @NatRevPhys]

Physics-driven learning for inverse problems in quantum chromodynamics https://t.co/5YzDIQU9gl