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Researchers from Ghent University and the University of Vienna have developed implicit differentiation techniques to stabilize gradient calculations in Projected Entangled-Pair States (PEPS) simulations. This approach addresses critical numerical instabilities inherent in automatic differentiation, offering improved scalability for optimizing variational quantum states without relying on costly subroutine-by-subroutine differentiation. The work provides explicit characteristic equations that simplify global gradient computation, directly advancing the reliability of algorithms used to model complex many-body quantum systems.
Ghent & Vienna Researchers Stabilize PEPS Gradients With Implicit Methods

Researchers from Ghent & Vienna stabilized calculations of PEPS gradients, a key challenge in variational optimization, using implicit differentiation techniques.
Researchers from Ghent University and the University of Vienna are addressing a critical limitation in the optimization of projected entangled-pair states (PEPS), a leading method for simulating complex quantum systems. While automatic differentiation is currently used to calculate energy gradients, the process is computationally expensive and prone to numerical instabilities, hindering reliable results. The team reformulated the gradient computation in terms of a single characteristic equation for the contraction environment, a shift designed to improve scaling with problem size. By choosing a suitable parametrization of this characteristic equation based on the intrinsic symmetries of the contraction environment, instabilities can be removed from the global gradient computation. Finally, the researchers provide…
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