
Explore the Agebc Bethe ansatz for open XXZ spin chains, focusing on non-diagonal boundary terms and Uqsl2 symmetry in condensed matter physics.

Explore integrability in condensed matter physics and quantum field theory, focusing on generalized fishnet conformal field theories.

Explore integrability in condensed matter physics and quantum field theory through geometrical web models, gaining insights from cutting-edge research.

Explore integrability in condensed matter physics and quantum field theory through an Ising-type formulation of the six-vertex model.

Explore quantum local charges in chiral affine Gaudin models, focusing on integrability in condensed matter physics and quantum field theory.

Explore computational approaches in quantum many-body physics, focusing on key highlights and advancements in the field.

Explore integrability in mathematical and theoretical physics with Didina Serban, delving into advanced concepts and their applications in modern research.

Explore the triviality of Ising SK TAP energy up to the AT line in spin glasses with F. Concetti from University of Basel.

Explore the intricate landscape complexity of elastic manifolds with Harvard researcher B. McKenna in this insightful workshop on spin glasses.

Explore quantum fluids of light in semiconductor lattices, focusing on photonic resonators, polariton condensates, and topological properties. Gain insights into driven dissipative physics and its applications.

Explore quantum spin liquids on triangular lattices using symmetry breaking and machine learning techniques to uncover novel states of matter.

Explore domain wall dynamics in 2D quantum Ising models using tree tensor networks, focusing on advanced computational techniques in condensed matter physics.

Explore reinforcement learning techniques for disentangling quantum states using partial observations, enhancing understanding of complex quantum systems.

Explore cutting-edge quantum simulations using optical lattices, delving into advanced techniques and applications in condensed matter physics.

Explore data-driven techniques for extracting crucial information from quantum many-body systems, enhancing understanding of complex quantum phenomena.

Explore effective Hamiltonians and complexity reconstruction in condensed matter physics, focusing on advanced theoretical concepts and applications.

Explore advanced techniques for optimizing neural network representations of quantum states, enhancing accuracy and efficiency in computational physics simulations.

Explore quantum many-body simulations leveraging artificial neural networks, gaining insights into advanced computational techniques for complex quantum systems.

Explore advanced techniques for simulating quantum many-body systems using neural quantum states, focusing on cutting-edge methodologies and applications.

Explore advanced techniques for simulating quantum many-body systems using neural quantum states, focusing on cutting-edge methodologies and applications.

Explore neural quantum states for simulating complex quantum systems, focusing on many-body interactions and advanced computational techniques.