Mehdi Soleimanifar

[Anthropic @AnthropicAI]

Introducing the Anthropic Science Blog.

Increasing the pace of scientific progress is a core part of Anthropic’s mission. The Science Blog will feature new research and stories of how scientists are using AI to accelerate their work.

Read the intro: https://t.co/1P9BDyX3xG

[The White House @WhiteHouse]

"Khamenei, one of the most evil people in History, is dead. This is not only Justice for the people of Iran, but for all Great Americans, and those people from many Countries throughout the World, that have been killed or mutilated by Khamenei..." - President Donald J. Trump

[Anthropic @AnthropicAI]

A statement from Anthropic CEO, Dario Amodei, on our discussions with the Department of War.

https://t.co/rM77LJejuk

[John Preskill @preskill]

Thanks, Ingrid Fadelli, for this nice article about our recently published paper with @RobertHuangHY and @MSoleimanifar. The paper describes a surprisingly simple protocol for verifying that a many-qubit state in the lab matches a desired target state.
https://t.co/nbUaNVUXwb

[Mehdi Soleimanifar @MSoleimanifar]

Happy to see that our work with @RobertHuangHY and @preskill is now published! We use shadow overlap to make machine learning of quantum systems verifiable, and to benchmark & optimize quantum circuits.

[Nature Physics @NaturePhysics]

The certification protocol presented here is an efficient way to verify that a many-qubit quantum state is close to a desired target state. As well as enabling the verification of near-term quantum devices, it has applications to quantum learning.
https://t.co/GT5llBsali

[PRX Quantum @PRX_Quantum]

Unconditional quantum advantage with random shallow Clifford circuits follows from the presence of long-range measurement-induced entanglement.

https://t.co/QufeuaVYx5

[Mehdi Soleimanifar @MSoleimanifar]

New joint work with Akshar Ramkumar on the mixing time of quantum Gibbs sampling for random sparse Hamiltonians.

Very proud of Akshar, who worked on this as a sophomore undergrad at Caltech!

https://t.co/IuHYvgzYCR

[Mehdi Soleimanifar @MSoleimanifar]

I had a great time working with Tai-Hsuan Yang, Thiago Bergamaschi, and John Preskill on this paper!

Special shoutout to Tai, who worked on this project as a SURF (Summer Undergraduate Research Fellow) at Caltech in the summer of 2023. 🏄

[Mehdi Soleimanifar @MSoleimanifar]

When can classical neural networks represent quantum states?

New joint work (https://t.co/YlXZlD7Isb) with Tai-Hsuan Yang, Thiago Bergamaschi, and John Preskill.🧵

[Mehdi Soleimanifar @MSoleimanifar]

See our paper for more on how the state's entanglement and sign structure affect conditional correlations.

There are many interesting questions in this area, especially around the theoretical foundations of neural quantum states and MIE.

It’s an exciting field to explore! 🤠

[Mehdi Soleimanifar @MSoleimanifar]

The connection between classical simulation algorithms and measurement-induced entanglement is fascinating and I’m excited about the next developments in this area! 😎

Thanks to my awesome collaborators for this fun research experience!

[Mehdi Soleimanifar @MSoleimanifar]

Why is it hard to classically sample from the output distribution of random quantum circuits?

In a joint work (https://t.co/KBekb78f3l) with Adam Bene Watts, David Gosset, and Yinchen Liu, we study this question, explore the physics behind it, and prove a quantum advantage.🧵

[Mehdi Soleimanifar @MSoleimanifar]

Also see this recent experimental study of measurement-induced entanglement in random quantum circuits by @GoogleQuantumAI:

https://t.co/hwFGB41OSR

[Google Quantum AI @GoogleQuantumAI]

Our paper, recently published in Nature, reveals how measurements affect a web of entangled qubits and for the first time, measurement induced quantum teleportation. ↓ https://t.co/eLOSDzC4Bh