most citedQuantum phase diagram of the spin- Heisenberg antiferromagnet on the square-kagome lattice: a tensor network study

1 citations · 1 across the 2 of their papers we have counts for

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9 papers

cond-mat.str-el20261 cited

Quantum phase diagram of the spin- Heisenberg antiferromagnet on the square-kagome lattice: a tensor network study

Saeed S. Jahromi, Yasir Iqbal

We study the ground-state phase diagram of the spin- antiferromagnetic Heisenberg model on the square-kagome lattice using infinite projected entangled-pair states (iPEPS). By…

quant-ph2026

Quantum Advantage: a Tensor Network Perspective

Augustine Kshetrimayum, Saeed S. Jahromi, Sukhbinder Singh +1

We review the recent quantum advantage experiments by IBM, D-Wave, and Google, focusing on cases where efficient classical simulations of the experiment were demonstrated or attemp…

cond-mat.str-el2024

Quantum Phase Diagram of the Bilayer Kitaev-Heisenberg Model

Elahe Samimi, Antonia Duft, Patrick Adelhardt +2

We study the ground-state phase diagram of the spin- Kitaev-Heisenberg model on the bilayer honeycomb lattice with large-scale tensor network calculations based on the infinit…

cond-mat.str-el2024

Valence-Bond Solid phases in the spin- Kekule-Heisenberg model

Fatemeh Mirmojarabian, Saeed S. Jahromi, Jahanfar Abouie

We map out the ground state phase diagram of the isotropic Kekule'-Kitaev model on the honeycomb lattice in the presence of the Heisenberg exchange couplings. Our study relies on l…

quant-ph2024

Quantum Large Language Models via Tensor Network Disentanglers

Borja Aizpurua, Saeed S. Jahromi, Fernando Loren +2

We introduce a framework for seamlessly integrating quantum computing into pretrained large language models (LLMs). The key idea is to construct a hybrid quantum-classical represen…

cs.CV2024

Tensor network compressibility of convolutional models

Sukhbinder Singh, Saeed S. Jahromi, Roman Orus

Convolutional neural networks (CNNs) are one of the most widely used neural network architectures, showcasing state-of-the-art performance in computer vision tasks. Although larger…