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Quantum Fisher information from randomized measurements

Quantum Physics · Submitted 27 May 2021

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Using randomized measurements we propose a protocol to accurately estimate these lower bounds in state-of-art quantum technological platforms.

how it is stated · asserted 0.77 read the record →

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arXiv ID2105.13164 (version 2)
Pith IDFLB726FZ, Pith's permanent record of this paper and its review
CitationAniket Rath, Anna Minguzzi, Beno\^it Vermersch, Cyril Branciard. "Quantum Fisher information from randomized measurements." arXiv:2105.13164 (2021). https://pith.science/paper/FLB726FZ
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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,232 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.11 · human participants 0.02 · controlled comparison 0.02 · randomized assignment 0.03 · states quantitative result 0.22 · compares with prior results 0.08 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

The quantum Fisher information (QFI) is a fundamental quantity of interest in many areas from quantum metrology to quantum information theory. It can in particular be used as a witness to establish the degree of multi-particle entanglement in quantum many-body-systems. In this work, we use polynomials of the density matrix to construct monotonically increasing lower bounds that converge to the QFI. Using randomized measurements we propose a protocol to accurately estimate these lower bounds in state-of-art quantum technological platforms. We estimate the number of measurements needed to achieve a given accuracy and confidence level in the bounds, and present two examples of applications of the method in quantum systems made of coupled qubits and collective spins.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The quantum Fisher information (QFI) is a fundamental quantity of interest in many areas from quantum metrology to quantum information theory. background 1.00 0.04 0.02 asserted 1.00
s1 It can in particular be used as a witness to establish the degree of multi-particle entanglement in quantum many-body-systems. background 1.00 0.05 0.04 hedged possibility 0.54
s2 In this work, we use polynomials of the density matrix to construct monotonically increasing lower bounds that converge to the QFI. contribution 0.64 0.94 0.43 asserted 1.00
s3 Using randomized measurements we propose a protocol to accurately estimate these lower bounds in state-of-art quantum technological platforms. method 0.89 0.87 0.21 asserted 0.77
s4 We estimate the number of measurements needed to achieve a given accuracy and confidence level in the bounds, and present two examples of applications of the method in quantum systems made of coupled qubits and collective spins. contribution 0.81 0.95 0.24 asserted 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from proof or derivation 0.89.

What was examined, and what was not

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  • C citations
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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

The quantum Fisher information (QFI) is a fundamental quantity of interest in many areas from quantum metrology to quantum information theory. It can in particular be used as a witness to establish the degree of multi-particle entanglement in quantum many-body-systems. In this work, we use polynomials of the density matrix to construct monotonically increasing lower bounds that converge to the QFI. Using randomized measurements we propose a protocol to accurately estimate these lower bounds in state-of-art quantum technological platforms. We estimate the number of measurements needed to achieve a given accuracy and confidence level in the bounds, and present two examples of applications of the method in quantum systems made of coupled qubits and collective spins.

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References
How later papers used it

58 later papers cite it

Evidence: substantial. 48 of the citing papers share no author with it, and 7 of those carry a confident label from Pith's citation classifier.

Pith read 14 of the 104 citing sentences, choosing only those whose citation markers point at this paper alone, and wrote the paraphrases from them. The summary, the counts, the evidence level, the links and the quotes come from code; the summary counts the papers listed below. A later paper is listed under a label when Pith's citation classifier gives one of its sentences that label at probability 0.8 or more (0.95 for support), Pith's reading finds that the citing paper itself did it, and a second check confirms the paraphrase against the sentence. This section lists uses only. It does not list criticism or disagreement, so their absence here says nothing about how the paper has been received. Papers that share an author with this one are listed apart, under "By the same authors". A quote is the citing authors' own sentence, shown when their paper's licence is CC BY, CC BY-SA or CC0. JSON

Uses its method or tool 2 of 5 papers with this label · 1 by the same authors

By the same authors

Compares with it 1 of 4 papers with this label
How the literature uses it

10 arXiv papers cite this in 14 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 8 sentences without a confident label

Builds on it 1 paper
Uses its method or tool 1 paper
  • Using Eq. [ref], the bound can be efficiently approximated on NISQ hardware: the QFIM can be estimated efficiently on a quantum device using techniques suggested in Ref. [ref] or Ref. [ref] using classical shadows.

    Avoiding barren plateaus using classical shadows · Bounding entanglement increase at a single optimization step · 0.97

Compares with it 1 paper
  • In contrast to the previous works utilizing randomized measurements to infer properties of many-body quantum states [ref] and (out-of-time-ordered) correlation functions of Heisenberg operators [ref] , the present protocol yields, with the SFF and PSFF, genuine properties of the time evolution operator.

    Probing many-body quantum chaos with quantum simulators · Synopsis · 0.96

Cites it as background 3 papers
  • Related randomized measurement protocols exist that construct lower bounds to the quantum Fisher information [ref] , while Krylov shadow tomography [ref] provides an efficient moment-based reconstruction of such quantities, though it requires multicopy snapshots [ref] .

    Certified Fidelity Susceptibility from Classical Shadows · Introduction · 0.88

  • The recent development of randomized measurements provides us with a general toolbox to measure in a state-agnostic way physical quantities associated with entanglement [ref] , scrambling [ref] , topological order [ref] , and in cross-device quantum verification [ref] .

    Importance sampling of randomized measurements for probing entanglement · Introduction · 0.84

  • Initially, randomized measurements have been proposed and experimentally implemented to characterize many-body quantum states [ref] and (out-of-time-ordered) correlation functions of Heisenberg operators [ref] .

    Probing many-body quantum chaos with quantum simulators · Randomized measurements of spectral form factors · 0.88

What it cites · 18 sentences without a confident label

Uses the method or tool of 3 papers
  • In the case of an a priori unknown noise channel, one can use again the formalism of robust shadows to correct our estimates of $F_n$ [ref] .

    Robust shadow estimation · Introduction · 0.94

  • In the case of an a priori unknown noise channel, one can use again the formalism of robust shadows to correct our estimates of $F_n$ [ref] .

    Classical Shadows With Noise · Introduction · 0.94

  • In the case of an a priori unknown noise channel, one can use again the formalism of robust shadows to correct our estimates of $F_n$ [ref] .

    Model-free readout-error mitigation for quantum expectation values · Introduction · 0.94

Cites as background 2 papers

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