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Maziar Farahzad

Publications and source records attributed to Maziar Farahzad.

3 recordsLinked to original sources

Smocked Metric Spaces and their Tangent Cones

We introduce the notion of a smocked metric spaces and explore the balls and geodesics in a collection of different smocked spaces. We find their rescaled Gromov-Hausdorff limits and prove these tangent cones at infinity exist, are unique, and are normed spaces. We close with a variety of open questions suitable for advanced undergraduates, masters students, and doctoral students.

math.MG↗

The Checkered Smocked Space and its Tangent Cone

Smocked metric spaces were first defined in arXiv:1906.03403 and it was proved that if a norm on the Euclidean space uniformly estimates the pseudometric of a smocked metric space, then the tangent cone at infinity is unique and is a norm vector space with that estimating norm. In this paper, we explicitly calculate the norm approximating the pseudometric of the checkered smocked space and find the tangent cone at infinity.

math.MG↗

Detector Tomography on IBM 5-qubit Quantum Computers and Mitigation of Imperfect Measurement

We use quantum detector tomography to characterize the qubit readout in terms of measurement POVMs on IBM Quantum Computers IBM Q 5 Tenerife and IBM Q 5 Yorktown. Our results suggest that the characterized detector model deviates from the ideal projectors by a few percent. Further improvement on this characterization can be made by adopting two- or more-qubit detector models instead of independent single-qubit detectors for all the qubits in one device. An unexpected behavior was seen in the physical qubit labelled as qubit 3 of IBM Q 5 Tenerife, which can be a consequence of detector crosstalk or qubit operations influencing each other and requires further investigation. This peculiar behavior is consistent with characterization from the more sophisticated approach of the gate set tomography. We also discuss how the characterized detectors' POVM, despite deviation from the ideal projectors, can be used to estimate the ideal detection distribution.

quant-ph↗