Published January 3, 2024 | Version v1

Data underpinning "Revealing measurement-induced phase transitions by pre-selection"

Description

We provide the raw data used to produce plots shown in our paper "Revealing measurement-induced phase transitions by pre-selection" and Jupyter Notebooks that where used to plot the data. We also provide code to show simulation details.

Abstract

Pushing forward the understanding of general non-unitary dynamics in controlled quantum platforms has been fueled by the recent discovery of measurement-induced phases and phase transitions. So far, these transitions remained largely elusive, since they are masked in standard quantum mechanical observables due to the randomness of measurement outcomes. Here, we establish a general scheme – pre-selection – to make them observable: The outcome randomness is broken explicitly by steering the system towards a representative state, which corresponds to one out of exponentially many possible measurement outcomes. Remarkably, this steering can be chosen so gently that the basic properties of the underlying measurement-induced transition, such as entanglement structure and critical exponents, are not modified. Pre-selection introduces a unique dark or absorbing state with macroscopic order, replacing the maximally mixed stationary state of the unconditioned measurement trajectory ensemble. This creates a link of measurement-induced phase transitions to new forms of quantum absorbing state transitions, which can be detected by standard means via a local order parameter. This insight further enables a quantum simulation strategy, determining the underlying universality class in state-of-the-art quantum platforms without measurement readout.

Files

Feedbackpaper.zip

Files (10.8 MB)

Name Size
md5:c00406461ea5f1f957c557cae14f4ab9
10.8 MB Preview Download

Additional details

Related works

Is metadata for
Preprint: 10.48550/arXiv.2208.10506 (DOI)

Funding

Deutsche Forschungsgemeinschaft
Excellence Strategy Cluster of Excellence Matter and Light for Quantum Computing (ML4Q) EXC 2004/1 390534769
Deutsche Forschungsgemeinschaft
Collaborative Research Center (CRC) 183 Project No. 277101999—project B02
European Research Council
Horizon 2020 research and innovation program 647434
Deutsche Forschungsgemeinschaft
SPP 1929 GiRyd DI 1745/2-1