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This research utilizes neural quantum states within a variational Monte Carlo framework to model the structural transitions of dipolar molecular droplets into crystals. By addressing strongly correlated regimes in quantum gases, the study provides critical insights into finite-size first-order phase transitions and supersolid states. These findings advance our understanding of how interaction strengths reorganize quantum ground states in isolated many-body systems.
Sources coveringarXiv, LessWrong
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How dipolar interactions structure molecular droplets

arXiv2 min read

arXiv:2609.05344v1 Announce Type: cross Abstract: We investigate how dipolar interactions between microwave-shielded polar molecules structure the self-bound droplets formed under variation of the interaction strength. We identify the transition from droplets to crystals as a finite-size first order transition. With droplet-ring states and transitional supersolid states we predict additional structure in the crystal and droplet phases, respectively. To describe this strongly correlated regime, and in particular the reconfiguration of quantum ground states, we design a variational Monte Carlo framework based on neural quantum states. It is especially suitable to describe ground states and almost degenerate states with very different configurations. Moreover, one can easily determine the superfluid fraction. Our results reveal the sequence of finite-size structures through which dipolar interactions reorganize molecular droplets into crystals.

Abstract:We investigate how dipolar interactions between microwave-shielded polar molecules structure the self-bound droplets formed under variation of the interaction strength. We identify the transition from droplets to crystals as a finite-size first order transition. With droplet-ring states and transitional supersolid states we predict additional structure in the crystal and droplet phases, respectively. To describe this strongly correlated regime, and in particular the reconfiguration of quantum ground states, we design a variational Monte Carlo framework based on neural quantum states. It is especially suitable to describe ground states and almost degenerate states with very different configurations. Moreover, one can easily determine the superfluid fraction. Our results reveal the sequence of finite-size structures through which dipolar interactions reorganize molecular droplets into crystals.

Quantum Gases (cond-mat.quant-gas); Quantum Physics (quant-ph)

arXiv:2609.05344 [cond-mat.quant-gas]

(or arXiv:2609.05344v1 [cond-mat.quant-gas] for this version)

https://doi.org/10.48550/arXiv.2609.05344 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 217 words

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