Evidence map›Paper›PMID 42164659›Full record

ArticleNature physics2026

Noise-induced shallow circuits and the absence of barren plateaus.

Antonio Anna Mele, Armando Angrisani, Soumik Ghosh, Sumeet Khatri, Jens Eisert, Daniel Stilck França, Yihui Quek

Abstract read
In one paragraph

Article in Nature physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Antonio Anna MeleDahlem Center for Complex Quantum Systems, Freie Universität Berlin, Berlin, Germany.ORCID 0000-0002-1009-7331
Armando AngrisaniLIP6, CNRS, Sorbonne Université, Paris, France.ORCID 0000-0002-7643-2892
Soumik GhoshDepartment of Computer Science, University of Chicago, Chicago, IL USA.
Sumeet KhatriDahlem Center for Complex Quantum Systems, Freie Universität Berlin, Berlin, Germany.ORCID 0000-0002-9858-0511
Jens EisertDahlem Center for Complex Quantum Systems, Freie Universität Berlin, Berlin, Germany.ORCID 0000-0003-3033-1292
Daniel Stilck FrançaDepartment of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-9699-5994
Yihui QuekDepartments of Mathematics and Physics, Massachusetts Institute of Technology, Cambridge, MA USA.ORCID 0000-0002-1227-0804

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Without a successful implementation of fault-tolerant quantum error correction, calculations on quantum computers are subject to noise that limits their capabilities. Here, motivated by realistic near-term hardware considerations, we study the impact of uncorrected local noise on logical quantum circuits. We first show that, in the task of estimating observable expectation values, any noise effectively truncates most quantum circuits to logarithmic depth. We then prove that quantum circuits under any non-unital noise do not exhibit barren plateaus for cost functions composed of local observables. However, by using the effective shallowness, we also design an efficient classical algorithm to estimate observable expectation values within any constant additive accuracy, with high probability over the choice of the circuit, in any circuit architecture. Taken together, our results establish that, unless we carefully engineer quantum circuits to take advantage of the noise, noisy quantum circuits are unlikely to offer an advantage over shallow ones for algorithms that output observable expectation value estimates, such as many variational quantum machine learning proposals.

Indexed as

Quantum informationQubits

Identifiers

PMID42164659
PMCPMC13183580

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.