Mehdi Soleimanifar

Mehdi Soleimanifar

Quantum Computing Researcher

I am an AWS Quantum Postdoctoral Scholar in the Institute for Quantum Information and Matter at Caltech hosted by John Preskill and Urmila Mahadev.

I recevied my PhD in physics from MIT under the supervision of Aram Harrow. I hold a BSc in electrical engineering and physics from Sharif University.

I am interested in quantum computing and quantum information science. My work draws on concepts from physics, computer science, and mathematics to develop theoretical frameworks that enable the learning and simulation of new features of physical systems using classical or quantum computers.

My PhD thesis:

Efficiently learning, testing, and simulating quantum many-body systems


Publications

* Indicates authors listed in alphabetical order.

  • Mixing time of quantum Gibbs sampling for random sparse Hamiltonians
    Akshar Ramkumar, Mehdi Soleimanifar
    (arXiv)
  • When can classical neural networks represent quantum states?
    Tai-Hsuan Yang, Mehdi Soleimanifar (co-first author), Thiago Bergamaschi, John Preskill
    (arXiv), (Summary), (Code)
  • Quantum advantage from measurement-induced entanglement in random shallow circuits
    Adam Bene Watts, David Gosset, Yinchen Liu, Mehdi Soleimanifar*
    (arXiv), (Summary)
  • Certifying almost all quantum states with few single-qubit measurements
    Hsin-Yuan Huang, John Preskill, Mehdi Soleimanifar*
    • In Symposium on Foundations of Computer Science (FOCS) 2024
    • Contributed talk at QIP 2024
    (arXiv), (Summary), (Slides), (Code)