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researcher

J. Eisert

43 papers hereh-index 293.3k citations77 works total

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

author position
  • first author2
  • middle author28
  • last author9

Across the 39 of 43 papers where every author was matched, so the position is known.

fields
  • quant-ph37
  • cs.IT4
  • cs.LG1
  • math.NA1
same name
  • J. Eisert — 49 papers, h 61
  • J. Eisert — 35 papers, h 29
  • J. Eisert — 18 papers, h 38
  • J. Eisert — 9 papers, h 11
  • J. Eisert — 8 papers, h 6
  • J. Eisert — 7 papers, h 9

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
20182026
most citedTensor network approaches for learning non-linear dynamical laws

11 citations · 37 across the 19 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

quant-ph2023

Quantum metrology in the finite-sample regime

Johannes Jakob Meyer, Sumeet Khatri, Daniel Stilck França +2

In quantum metrology, one of the major applications of quantum technologies, the ultimate precision of estimating an unknown parameter is often stated in terms of the Cramér-Rao bo…

quant-ph2023

Verifiable measurement-based quantum random sampling with trapped ions

Martin Ringbauer, Marcel Hinsche, Thomas Feldker +13

Quantum computers are now on the brink of outperforming their classical counterparts. One way to demonstrate the advantage of quantum computation is through quantum random sampling…

quant-ph2023

Quantum complexity phase transitions in monitored random circuits

Ryotaro Suzuki, Jonas Haferkamp, Jens Eisert +1

Recently, the dynamics of quantum systems that involve both unitary evolution and quantum measurements have attracted attention due to the exotic phenomenon of measurement-induced…

quant-ph2023

On the average-case complexity of learning output distributions of quantum circuits

Alexander Nietner, Marios Ioannou, Ryan Sweke +4

In this work, we show that learning the output distributions of brickwork random quantum circuits is average-case hard in the statistical query model. This learning model is widely…

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