Annabelle Bohrdt
557 posts
@aBohrdt
Theoretical physicist @uni_regensburg and @MCQST_cluster, machine learning, strongly correlated systems & quantum simulation
More holiday reading 🎄📚 🎁 observing the formation of stripes 🦓 in a quantum gas microscope 🔬— read all about what we can learn about stripes if we look very closely 🔎 and at higher order correlations ⬆️🟡⬇️ here arxiv.org/abs/2312.14156 @MCQST_cluster @uni_regensburg
Do you want to realize and probe 🔬 long-range superconducting order with repulsively interacting fermions in your lattice quantum simulator? We got you covered — read our proposal here: arxiv.org/abs/2406.02551 led by @henningschlmr and Hannah Lange @MCQST_cluster @QManyBody
The 2024 #NobelPrize laureates in physics used tools from physics to construct methods that helped lay the foundation for today’s powerful machine learning. John Hopfield created a structure that can store and reconstruct information. Geoffrey Hinton invented a method that can independently discover properties in data and which has become important for the large artificial neural networks now in use. Although computers cannot think, machines can now mimic functions such as memory and learning. This year’s physics laureates have helped make this possible. Using fundamental concepts and methods from physics, they have developed technologies that use structures in networks to process information.
Check out the new version of our review — including a few new parts 🤖 : choice of architecture over time 🗓️& performance on ground state search of the J1-J2 model with different architectures 🚀
Another very nice visit to 🤓@Perimeter and @UWaterloo 🇨🇦 with beautiful fall weather 🍁
