# Learnability of the output distributions of local quantum circuits

@article{Hinsche2021LearnabilityOT, title={Learnability of the output distributions of local quantum circuits}, author={Marcel Hinsche and Marios Ioannou and A. Nietner and Jonas Haferkamp and Yihui Quek and Dominik Hangleiter and Jean-Pierre Seifert and Jens Eisert and Ryan Sweke}, journal={ArXiv}, year={2021}, volume={abs/2110.05517} }

M. Hinsche, M. Ioannou, A. Nietner, J. Haferkamp, 2 Y. Quek, 1 D. Hangleiter, 1 J.-P. Seifert, 6 J. Eisert, 2, 7 and R. Sweke Dahlem Center for Complex Quantum Systems, Freie Universität Berlin, 14195 Berlin, Germany Helmholtz-Zentrum Berlin für Materialien und Energie, 14109 Berlin, Germany Information Systems Laboratory, Stanford University, Stanford, CA 94305, USA Joint Center for Quantum Information and Computer Science (QuICS), University of Maryland and NIST, College Park, MD 20742, USA…

## 5 Citations

Complexity phase transitions in instantaneous quantum polynomial-time circuits

- Physics
- 2022

We study a subclass of the Instantaneous Quantum Polynomial-time (IQP) circuit with a varying density of two-qubit gates. We identify two phase transitions as a function of the gate density. At the…

Equivariant Quantum Graph Circuits

- Computer ScienceArXiv
- 2021

This work proposes equivariant quantum graph circuits (EQGCs), as a class of parameterized quantum circuits with strong relational inductive bias for learning over graph-structured data, and proves that the subclasses of interest are universal approximators for functions over the bounded graph domain.

Learning Classical Readout Quantum PUFs based on single-qubit gates

- Computer Science, PhysicsArXiv
- 2021

This work formalizes the class of Classical Readout Quantum PUFs (CR-QPUFs) using the statistical query (SQ) model and explicitly shows insuﬃcient security for CR-Q PUFs based on single qubit rotation gates, when the adversary has SQ access to the CR-ZPUF.

Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps

- Computer Science
- 2022

It is proved that a wide class of variational quantum models—which are shallow, and exhibit no barren plateus—have only a superpolynomially small fraction of local minima within any constant energy from the global minimum, rendering these models untrainable if no good initial guess of the optimal parameters is known.

Evaluating Generalization in Classical and Quantum Generative Models

- Computer ScienceArXiv
- 2022

Using the sample-based generalization metrics proposed here, any generative model, from state-of-the-art classical generative models such as GANs to quantum models, can be evaluated on the same ground on a concrete well-defined framework and foresee these metrics as valuable tools for rigorously defining practical quantum advantage in the domain of generative modeling.

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