Just published in @PhysRevB—take a look:

🚀 Introducing SymBasis.jl: Easily generate symmetry-preserving bases for quantum many-body systems—custom or predefined symmetries, simple interface, minimal effort. #JuliaLang @JuliaLanguage #Physics #ScientificComputing https://t.co/rCdGO0qmoc

#PRBTopDownload: Hierarchy of timescales in a disordered #spin-1/2 XX ladder Kadir Çeven, Lukas Peinemann, and Fabian Heidrich-Meisner Phys. Rev. B 113, 045126 ➡️ https://t.co/w6r1xmrsrk #OpenAccess #condmat #physics @APSPhysics

TL;DR in meme form👇(3/3)

Also, unlike other non-integrable models, spin diffuses faster than energy in this model. (2/3)

🚨 New on @arxiv: https://t.co/Jm9QMM3F4d 
Relaxation timescales govern non‑equilibrium dynamics of closed many‑body quantum systems. In a disordered spin‑1/2 XX ladder, we show that the RMT time ∝ L² and it upper‑bounds the Thouless times. (1/3)

We wrote a short review on neural quantum states 🤖 ⚛️ The goal is to give a concise overview of architectures and applications — we hope this will be particularly useful for people starting out in the field 🤓 check it out: https://t.co/nLw5gtKf7H @uni_regensburg @MCQST_cluster

A big thank you to my advisors (@OktelOzgur and Ahmet Keleş) for their invaluable contributions to this article! It was a great experience and journey to write and publish this article. #coauthors #publication #collaboration #PRA

Our paper highlights the potential of neural-network quantum states as a promising tool for tackling some of the most challenging problems in strongly correlated quantum matter. #quantumphysics #newarticle #PRA

In the weak coupling limit, neural networks also diagnose other many-body phenomena such as the vortex, chiral, and biased-ladder phases. #physics #newfindings #PRA

Our work demonstrates that variational neural networks can reliably predict the superfluid-Mott insulator phase diagram in the strong coupling limit, comparable with the accuracy of the density-matrix renormalization group. #quantumphysics #newresearch #PRA

In this paper, we investigate the use of neural-network quantum states in ladder models, specifically the two-leg Bose-Hubbard ladder under strong synthetic magnetic fields. #physics #research #quantumphysics #machinelearning #neuralnetworks #PRA

🚨 Just released in @PhysRevA 🚨 Thrilled to announce the release of our latest paper on using neural-network quantum states in the two-leg Bose-Hubbard ladder under magnetic flux. Check it out! https://t.co/rDgi9t4DEB