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20232026
most citedMachine Learning for Practical Quantum Error Mitigation

63 citations · 197 across the 17 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

quant-ph2025

Big cats: entanglement in 120 qubits and beyond

Ali Javadi-Abhari, Simon Martiel, Alireza Seif +2

Entanglement is the quintessential quantum phenomenon and a key enabler of quantum algorithms. The ability to faithfully entangle many distinct particles is often used as a benchma…

quant-ph2025

Theory and Architecture of Syndrome-Resolved Logical Gates

Nobuyuki Yoshioka, Alireza Seif, Peter Groszkowski +2

We introduce a general framework for weak transversal gates, namely syndrome-resolved implementation of logical unitaries realized by local physical unitaries, and demonstrate its…

quant-ph2025

Enhancing quantum noise characterization via extra energy levels

Senrui Chen, Akel Hashim, Noah Goss +3

Noise is a major challenge for building practical quantum computing systems. Precise characterization of quantum noise is crucial for developing effective error mitigation and corr…

quant-ph2025

Disambiguating Pauli noise in quantum computers

Edward H. Chen, Senrui Chen, Laurin E. Fischer +7

To successfully perform quantum computations, it is often necessary to first accurately characterize the noise in the underlying hardware. However, it is well known that fundamenta…

quant-ph2025★ 5 cited

Efficient Lindblad synthesis for noise model construction

Moein Malekakhlagh, Alireza Seif, Daniel Puzzuoli +2

Effective noise models are essential for analyzing and understanding the dynamics of quantum systems, particularly in applications like quantum error mitigation and correction. How…