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DTSTART:20230312T070000
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DTSTART:20231105T060000
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DTSTART;TZID=America/Toronto:20240110T120000
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URL:https://uwaterloo.ca/institute-for-quantum-computing/events/iqc-student
 -seminar-featuring-senrui-chen-university-chicago
LOCATION:QNC - Quantum Nano Centre 200 University Avenue West QNC 1201 Wate
 rloo ON N2L 3G1 Canada
SUMMARY:IQC Student Seminar Featuring Senrui Chen\, University of Chicago
CLASS:PUBLIC
DESCRIPTION:TIGHT BOUNDS FOR PAULI CHANNEL LEARNING WITH AND WITHOUT ENTANG
 LEMENT\n\nQuantum Nano Centre\, 200 University Ave West\, Room QNC 1201\nW
 aterloo\, ON CA N2L 3G1\n\nQuantum entanglement is a crucial resource for 
 learning properties\nfrom nature\, but a precise characterization of its a
 dvantage can be\nchallenging. In this work\, we consider learning algorith
 ms without\nentanglement as those that only utilize separable states\,\nme
 asurements\, and operations between the main system of interest and\nan an
 cillary system. Interestingly\, these algorithms are equivalent to\nthose 
 that apply quantum circuits on the main system interleaved with\nmid-circu
 it measurements and classical feedforward. Within this\nsetting\, we prove
  a tight lower bound for Pauli channel learning\nwithout entanglement that
  closes the gap between the best-known upper\nbound. In particular\, we sh
 ow that Θ(n^2/_ε_^2) rounds of\nmeasurements are required to estimate ea
 ch eigenvalue of an n-qubit\nPauli channel to _ε_ error with high proba
 bility when learning\nwithout entanglement. In contrast\, a learning algor
 ithm with\nentanglement only needs Θ(1/_ε_^2) copies of the Pauli channe
 l. Our\nresults strengthen the foundation for an entanglement-enabled\nadv
 antage for Pauli noise characterization. We will talk about\nongoing expe
 rimental progress in this direction.\n\nREFERENCE: Mainly based on [arXiv:
  2309.13461]
DTSTAMP:20260405T053025Z
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