Synergistic pretraining of parametrized quantum circuits via tensor ...

Parametrized quantum circuits (PQCs) represent a promising framework for using present-day quantum hardware to solve diverse problems in ...

A “synergistic” approach is introduced that addresses two prominent issues withParametrized quantum circuits: the prevalence of barren plateaus in PQC ...

Synergy Between Quantum Circuits and Tensor Networks - arXiv

Proposals for attaining practical quantum advantage typically involve parametrized quantum circuits (PQCs), whose parameters can be ...

Synergistic pretraining of parametrized quantum circuits via tensor ...

In many settings --- most prominently in so-called parametrized or variational algorithms --- the objective function is a result of hybrid quantum-classical ...

Synergistic pretraining of parametrized quantum circuits via tensor ...

Article on Synergistic pretraining of parametrized quantum circuits via tensor networks, published in Nature Communications 14 on 2023-12-15 by Manuel S ...

Synergistic pretraining of parametrized quantum circuits via tensor ...

AbstractParametrized quantum circuits (PQCs) represent a promising framework for using present-day quantum hardware to solve diverse problems in materials ...

Quantum Generative AI Research in Nature Communications

The article, titled “Synergistic pretraining of parametrized quantum circuits via tensor networks,” demonstrates how quantum circuits can ...

Synergistic pretraining of parametrized quantum circuits via tensor ...

AbstractParametrized quantum circuits (PQCs) represent a promising framework for using present-day quantum hardware to solve diverse problems in materials ...

arXiv:2208.13673v2 [quant-ph] 24 Aug 2023

Synergy Between Quantum Circuits and Tensor Networks: Short-cutting ... barren plateaus in parametrized quantum circuits,” Quantum 3,. 214 (2019).

Zapata AI Researchers Show How Quantum Circuits Can Improve ...

The article, titled “Synergistic pretraining of parametrized quantum circuits via tensor networks,” demonstrates how quantum circuits can extend and complement ...

Synergy Between Quantum Circuits and Tensor Networks - IPAM at ...

... Quantum Systems via Classical and Quantum Computation Workshop. Abstract: Parametrized quantum circuits (PQCs) represent a promising ...

Zapata AI's Quantum-Enhanced Generative AI Research Published ...

The paper, titled “Synergistic pretraining of parametrized quantum circuits via tensor networks,” explores how quantum circuits can augment ...

Manuel Rudolph on X: "Can VQAs with barren plateaus still be ...

Synergistic pretraining of parametrized quantum circuits via tensor networks · From nature.com · 9:22 AM · Dec 18, 2023. ·. 12.6K. Views. 16. Reposts.

‪Jing Chen‬ - ‪Google Scholar‬

Synergistic pretraining of parametrized quantum circuits via tensor networks. MS Rudolph, J Miller, D Motlagh, J Chen, A Acharya, A Perdomo-Ortiz. Nature ...

Schematic depiction of the synergistic training framework utilizing ...

Synergistic pretraining of parametrized quantum circuits via tensor networks ... ... a) Quantum Circuit Initialization and Actor Network: Quantum circuits, ...

A joint optimization approach of parameterized quantum circuits with ...

A joint optimization approach of parameterized quantum circuits with a tensor ... Synergistic pretraining of parametrized quantum circuits via tensor networks.

Tight and Efficient Gradient Bounds for Parameterized Quantum ...

``Synergistic pretraining of parametrized quantum circuits via tensor networks''. ... parameterized quantum circuits via reduced-domain parameter ...

‪Atithi Acharya‬ - ‪Google Tudós‬ - Google Scholar

Synergistic pretraining of parametrized quantum circuits via tensor networks. MS Rudolph, J Miller, D Motlagh, J Chen, A Acharya, A Perdomo-Ortiz. Nature ...

‪Jacob Miller‬ - ‪Google Scholar‬

Synergistic pretraining of parametrized quantum circuits via tensor networks. MS Rudolph, J Miller, D Motlagh, J Chen, A Acharya, A Perdomo-Ortiz. Nature ...

Manuel Rudolph posted on the topic | LinkedIn

Our work on synergistic pretraining of quantum circuits via tensor ... parametrized quantum circuit into a promising region in the loss ...