A survey on the complexity of learning quantum states

A Anshu, S Arunachalam - Nature Reviews Physics, 2024‏ - nature.com
Quantum learning theory is a new and very active area of research at the intersection of
quantum computing and machine learning. Important breakthroughs in the past two years …

Random unitaries in extremely low depth

T Schuster, J Haferkamp, HY Huang - arxiv preprint arxiv:2407.07754, 2024‏ - arxiv.org
We prove that random quantum circuits on any geometry, including a 1D line, can form
approximate unitary designs over $ n $ qubits in $\log n $ depth. In a similar manner, we …

On the role of entanglement and statistics in learning

S Arunachalam, V Havlicek… - Advances in Neural …, 2024‏ - proceedings.neurips.cc
In this work we make progress in understanding the relationship between learning models
when given access to entangled measurements, separable measurements and statistical …

Quantum Information Processing, Sensing, and Communications: Their Myths, Realities, and Futures

L Hanzo, Z Babar, Z Cai, D Chandra… - Proceedings of the …, 2025‏ - ieeexplore.ieee.org
The recent advances in quantum information processing, sensing, and communications are
surveyed with the objective of identifying the associated knowledge gaps and formulating a …

Learning unitaries with quantum statistical queries

A Angrisani - arxiv preprint arxiv:2310.02254, 2023‏ - arxiv.org
We propose several algorithms for learning unitary operators from quantum statistical
queries (QSQs) with respect to their Choi-Jamiolkowski state. Quantum statistical queries …

Learning quantum processes with quantum statistical queries

C Wadhwa, M Doosti - arxiv preprint arxiv:2310.02075, 2023‏ - arxiv.org
Learning complex quantum processes is a central challenge in many areas of quantum
computing and quantum machine learning, with applications in quantum benchmarking …

Quantum local differential privacy and quantum statistical query model

A Angrisani, E Kashefi - arxiv preprint arxiv:2203.03591, 2022‏ - arxiv.org
Quantum statistical queries provide a theoretical framework for investigating the
computational power of a learner with limited quantum resources. This model is particularly …

Local random quantum circuits form approximate designs on arbitrary architectures

S Mittal, N Hunter-Jones - arxiv preprint arxiv:2310.19355, 2023‏ - arxiv.org
We consider random quantum circuits (RQC) on arbitrary connected graphs whose edges
determine the allowed $2 $-qudit interactions. Prior work has established that such $ n …

Latent Style-based Quantum GAN for high-quality Image Generation

SY Chang, S Thanasilp, BL Saux, S Vallecorsa… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Quantum generative modeling is among the promising candidates for achieving a practical
advantage in data analysis. Nevertheless, one key challenge is to generate large-size …

Agnostic process tomography

C Wadhwa, L Lewis, E Kashefi, M Doosti - arxiv preprint arxiv:2410.11957, 2024‏ - arxiv.org
Characterizing a quantum system by learning its state or evolution is a fundamental problem
in quantum physics and learning theory with a myriad of applications. Recently, as a new …