Demonstration of Robust and Efficient Quantum Property Learning with Shallow Shadows

no code implementations • 27 Feb 2024 • Hong-Ye Hu, Andi Gu, Swarnadeep Majumder, Hang Ren, Yipei Zhang, Derek S. Wang, Yi-Zhuang You, Zlatko Minev, Susanne F. Yelin, Alireza Seif

This combined theoretical and experimental analysis positions the robust shallow shadow protocol as a scalable, robust, and sample-efficient protocol for characterizing quantum states on current quantum computing platforms.

Bayesian Inference

Machine Learning for Practical Quantum Error Mitigation

2 code implementations • 29 Sep 2023 • Haoran Liao, Derek S. Wang, Iskandar Sitdikov, Ciro Salcedo, Alireza Seif, Zlatko K. Minev

Here, through experiments on state-of-the-art quantum computers using up to 100 qubits, we demonstrate that without sacrificing accuracy machine learning for quantum error mitigation (ML-QEM) drastically reduces the cost of mitigation.

The impact of memory on learning sequence-to-sequence tasks

1 code implementation • 29 May 2022 • Alireza Seif, Sarah A. M. Loos, Gennaro Tucci, Édgar Roldán, Sebastian Goldt

Here, we propose a simple model for a seq2seq task that has the advantage of providing explicit control over the degree of memory, or non-Markovianity, in the sequences -- the stochastic switching-Ornstein-Uhlenbeck (SSOU) model.

Machine Translation