Evidence map›Paper›PMID 41969574›Full record

ArticlePNAS nexus2026

Measurement-induced phase transitions in informational active matter.

Bryan VanSaders, Michel Fruchart, Vincenzo Vitelli

Abstract read
In one paragraph

Article in PNAS nexus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Bryan VanSadersJames Franck Institute, The University of Chicago, Chicago, IL 60637, USA.
Michel FruchartGulliver, ESPCI Paris, Université PSL, CNRS, Paris 75005, France.
Vincenzo VitelliJames Franck Institute, The University of Chicago, Chicago, IL 60637, USA.ORCID https://orcid.org/0000-0001-6328-8783

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Various biological and synthetic media out of equilibrium can be viewed as many-ratchet systems that rectify environmental noise through local measurements and information processing, like Maxwell's prototypical demon. These systems pose a challenge to standard coarse-graining approaches because they are described in terms of decision-making protocols similar to computer programs rather than force laws. Here, we study a many-body generalization of the Maxwell demon problem: a fluid composed of adaptive particles that achieve collective behavior by biasing noise-driven scattering events subject to measurements. Using a combination of information-theoretic, kinetic, and hydrodynamic tools, we elucidate how microscopic decision-making protocols, rather than microscopic forces, generate macroscopic active states sustained by continuous measurements. These include an informational version of flocking whose order parameter is bounded by the information measured, and the onset of which may be viewed as a measurement-induced phase transition. We find that the signature of such microscopic choices is an "informational activity" that selectively compresses phase space, without work, and causes deviations from equilibrium scaling with the magnitude of environmental noise. We envision applications to noise-induced patterning performed by collections of microrobots guided by reinforcement learning or programmable phoretic colloids in turbulent flows that exploit local measurements and control actions to counteract the scrambling of information by chaos.

Indexed as

active matterflockinginformation enginesmeasurement-induced phase transitionsreinforcement learning

Identifiers

PMID41969574
PMCPMC13069901

What OpenQuestion holds

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Registered trials

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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.