Near-Term Fermionic Simulation with Subspace Noise Tailored Quantum Error Mitigation

Fuente: arXiv
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Autores principales: Papič, Miha, Algaba, Manuel G., Godinez-Ramirez, Emiliano, de Vega, Inés, Auer, Adrian, Šimkovic IV, Fedor, Calzona, Alessio
Formato: Preprint
Publicado: 2025
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author Papič, Miha
Algaba, Manuel G.
Godinez-Ramirez, Emiliano
de Vega, Inés
Auer, Adrian
Šimkovic IV, Fedor
Calzona, Alessio
author_facet Papič, Miha
Algaba, Manuel G.
Godinez-Ramirez, Emiliano
de Vega, Inés
Auer, Adrian
Šimkovic IV, Fedor
Calzona, Alessio
contents Quantum error mitigation (QEM) has emerged as a powerful tool for the extraction of useful quantum information from quantum devices. Here, we introduce the Subspace Noise Tailoring (SNT) algorithm, which efficiently combines the cheap cost of Symmetry Verification (SV) and low bias of Probabilistic Error Cancellation (PEC) QEM techniques. We study the performance of our method by simulating the Trotterized time evolution of the spin-1/2 Fermi-Hubbard model (FHM) using a variety of local fermion-to-qubit encodings, which define a computational subspace through a set of stabilizers, the measurement of which can be used to post-select noisy quantum data. We study different combinations of QEM and encodings and uncover a rich state diagram of optimal combinations, depending on the hardware performance, system size and available shot budget. We then demonstrate how SNT extends the reach of current noisy quantum computers in terms of the number of fermionic lattice sites and the number of Trotter steps, and quantify the required hardware performance beyond which a noisy device may compete with current state-of-the-art classical computational methods.
format Preprint
id arxiv_https___arxiv_org_abs_2503_11785
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Near-Term Fermionic Simulation with Subspace Noise Tailored Quantum Error Mitigation
Papič, Miha
Algaba, Manuel G.
Godinez-Ramirez, Emiliano
de Vega, Inés
Auer, Adrian
Šimkovic IV, Fedor
Calzona, Alessio
Quantum Physics
Strongly Correlated Electrons
Quantum error mitigation (QEM) has emerged as a powerful tool for the extraction of useful quantum information from quantum devices. Here, we introduce the Subspace Noise Tailoring (SNT) algorithm, which efficiently combines the cheap cost of Symmetry Verification (SV) and low bias of Probabilistic Error Cancellation (PEC) QEM techniques. We study the performance of our method by simulating the Trotterized time evolution of the spin-1/2 Fermi-Hubbard model (FHM) using a variety of local fermion-to-qubit encodings, which define a computational subspace through a set of stabilizers, the measurement of which can be used to post-select noisy quantum data. We study different combinations of QEM and encodings and uncover a rich state diagram of optimal combinations, depending on the hardware performance, system size and available shot budget. We then demonstrate how SNT extends the reach of current noisy quantum computers in terms of the number of fermionic lattice sites and the number of Trotter steps, and quantify the required hardware performance beyond which a noisy device may compete with current state-of-the-art classical computational methods.
title Near-Term Fermionic Simulation with Subspace Noise Tailored Quantum Error Mitigation
topic Quantum Physics
Strongly Correlated Electrons
url https://arxiv.org/abs/2503.11785