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Muhammad Usman

15 papers hereh-index 597 citations16 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5
  • last author10

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • quant-ph13
  • cond-mat.str-el1
  • physics.flu-dyn1
same name
  • Muhammad Usman — 11 papers, h 12
  • Muhammad Usman — 10 papers, h 17
  • Muhammad Usman — 10 papers, h 3
  • Muhammad Usman — 9 papers, h 10
  • Muhammad Usman — 8 papers, h 7
  • Muhammad Usman — 8 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedCalibrating the role of entanglement in variational quantum circuits

21 citations · 51 across the 14 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

quant-ph2024★ 2 cited

Magic State Injection on IBM Quantum Processors Above the Distillation Threshold

Younghun Kim, Martin Sevior, Muhammad Usman

The surface code family is a promising approach to implementing fault-tolerant quantum computations. Universal fault-tolerance requires error-corrected non-Clifford operations, in…

quant-ph2024★ 16 cited

Stabilizer Tensor Networks with Magic State Injection

Azar C. Nakhl, Ben Harper, Maxwell West +4

This work augments the recently introduced Stabilizer Tensor Network (STN) protocol with magic state injection, reporting a new framework with significantly enhanced ability to sim…

quant-ph2024★ 2 cited

Transversal CNOT gate with multi-cycle error correction

Younghun Kim, Martin Sevior, Muhammad Usman

A scalable and programmable quantum computer holds the potential to solve computationally intensive tasks that classical computers cannot accomplish within a reasonable time frame,…

quant-ph2024★ 8 cited

Adversarial Robustness Guarantees for Quantum Classifiers

Neil Dowling, Maxwell T. West, Angus Southwell +4

Despite their ever more widespread deployment throughout society, machine learning algorithms remain critically vulnerable to being spoofed by subtle adversarial tampering with the…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.