8 citations · 10 across the 12 of their papers we have counts for
4 papers · 1 filter
Topology Obstructs Pure Foundation Neural Quantum States
Timothy Heightman, Elena Orlova, Philip Mantrov +1
Foundation models for ground states in spin-1/2 systems are a promising method for problems ranging from quantum chemistry to identifying new phase diagrams. Nearly all such models…
Hamilton-Zero: A Neural Tensor-Network Foundation Model for Ground States of Arbitrary Quadratic Qubit Hamiltonians
Timothy Heightman, Elena Orlova, Philip Mantrov +1
A central promise of useful quantum advantage is the ability to compute ground states of Hamiltonian systems beyond the reach of classical simulation methods. Here we demonstrate t…
Lie-Algebraic Classical Simulation of Bosonic Systems Beyond Gaussian Dynamics
Adelina Bärligea, Timothy Heightman, Jakob S. Kottmann +1
Classical simulability is ultimately determined by both the dynamics of a quantum system and the observables being evaluated. Lie-algebraic simulation exploits the latter to make e…
Lindbladian Learning with Neural Differential Equations
Timothy Heightman, Roman Aseguinolaza Gallo, Edward Jiang +3
Inferring the dynamical generator of a many-body quantum system from measurement data is essential for the verification, calibration, and control of quantum processors. When the sy…