Energy eigenvalues of a Hamiltonian can be extracted from real-time correlator matrices via a generalized eigenvalue problem, and the method outperforms Fourier analysis on a quantum computer.
Qubit regularized $O(N)$ nonlinear sigma models
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abstract
Motivated by the prospect of quantum simulation of quantum field theories, we formulate the $O(N)$ nonlinear sigma model as a "qubit" model with an $(N+1)$-dimensional local Hilbert space at each lattice site. Using an efficient worm algorithm in the worldline formulation, we demonstrate that the model has a second-order critical point in $(2+1)$ dimensions, where the continuum physics of the nontrivial $O(N)$ Wilson-Fisher fixed point is reproduced. We compute the critical exponents $\nu$ and $\eta$ for the $O(N)$ qubit models up to $N=8$, and find excellent agreement with known results in literature from various analytic and numerical techniques for the $O(N)$ Wilson-Fisher universality class. Our models are suited for studying $O(N)$ nonlinear sigma models on quantum computers up to $N=8$ in $d=2,3$ spatial dimensions.
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Hamiltonian spectra in quantum computers through the generalized eigenvalue method
Energy eigenvalues of a Hamiltonian can be extracted from real-time correlator matrices via a generalized eigenvalue problem, and the method outperforms Fourier analysis on a quantum computer.