806 citations · 5.4k across the 44 of their papers we have counts for
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Effect of barren plateaus on gradient-free optimization
Andrew Arrasmith, M. Cerezo, Piotr Czarnik +2
Barren plateau landscapes correspond to gradients that vanish exponentially in the number of qubits. Such landscapes have been demonstrated for variational quantum algorithms and q…
Non-trivial symmetries in quantum landscapes and their resilience to quantum noise
Enrico Fontana, M. Cerezo, Andrew Arrasmith +2
Very little is known about the cost landscape for parametrized Quantum Circuits (PQCs). Nevertheless, PQCs are employed in Quantum Neural Networks and Variational Quantum Algorithm…
Absence of Barren Plateaus in Quantum Convolutional Neural Networks
Arthur Pesah, M. Cerezo, Samson Wang +3
Quantum neural networks (QNNs) have generated excitement around the possibility of efficiently analyzing quantum data. But this excitement has been tempered by the existence of exp…
Noise-Induced Barren Plateaus in Variational Quantum Algorithms
Samson Wang, Enrico Fontana, M. Cerezo +4
Variational Quantum Algorithms (VQAs) may be a path to quantum advantage on Noisy Intermediate-Scale Quantum (NISQ) computers. A natural question is whether noise on NISQ devices p…
Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets
Kunal Sharma, M. Cerezo, Zoë Holmes +3
The no-free-lunch (NFL) theorem is a celebrated result in learning theory that limits one's ability to learn a function with a training data set. With the recent rise of quantum ma…
Trainability of Dissipative Perceptron-Based Quantum Neural Networks
Kunal Sharma, M. Cerezo, Lukasz Cincio +1
Several architectures have been proposed for quantum neural networks (QNNs), with the goal of efficiently performing machine learning tasks on quantum data. Rigorous scaling result…