From the 1 of 15 linked papers with an AI index.
15 papers
Approximate sampling from decoded quantum interferometry via Markov chain Monte Carlo methods
Elies Gil-Fuster, Matan Ninio, Lennart Bittel +4
The paper investigates whether classical Markov chain Monte Carlo methods, especially block‑Gibbs sampling, can reproduce the optimization performance of decoded quantum interferom…
Cautious optimism for deep parameterized quantum circuits
Marie Kempkes, Elies Gil-Fuster, Carlos Bravo-Prieto +5
A central challenge in quantum machine learning is understanding the scaling behavior of parameterized quantum circuits (PQCs). In particular, it remains unclear how their performa…
Provable learning separation for predicting time-evolution of quantum many-body systems
Rahul Bandyopadhyay, Riccardo Molteni, Jens Eisert +2
Given that quantum computers are naturally suited to simulate the behavior of quantum many-body systems, an immediate question arises: can one formulate physically motivated quantu…
Optimal stellar rank approximation of squeezed cat states with photon catalysis
Julian K. Nauth, Nathan Walk, Ananga M. Datta +4
Non-Gaussian quantum states and operations constitute essential resources for achieving quantum computational advantage and enabling quantum error correction in bosonic platforms.…
No Universal Purification in Quantum Mechanics
Zhenhuan Liu, Zhenyu Du, Jens Eisert +2
Many central tasks in fundamental physics and quantum information processing are possible only insofar as mixed quantum states can be made purer. In this work, we prove that the li…
Non-Clifford Cost of Random Unitaries
Lorenzo Leone, Salvatore F. E. Oliviero, Alioscia Hamma +2
Recent years have enjoyed a strong interest in exploring properties and applications of random quantum circuits. In this work, we explore the ensemble of -doped Clifford circuit…