Spectral Gap Amplification
Rolando D. Somma, Sergio Boixo

TL;DR
This paper introduces a method for quadratic spectral gap amplification in frustration-free Hamiltonians, enabling faster quantum algorithms and highlighting fundamental limits in quantum-classical simulation methods.
Contribution
It demonstrates quadratic spectral gap amplification for frustration-free Hamiltonians and proves its optimality, revealing limits of classical simulation techniques.
Findings
Quadratic amplification is possible for frustration-free Hamiltonians.
No general spectral gap amplification is possible without the frustration-free property.
Finding a similarity transformation between certain Hamiltonians and stochastic matrices is computationally hard.
Abstract
A large number of problems in science can be solved by preparing a specific eigenstate of some Hamiltonian H. The generic cost of quantum algorithms for these problems is determined by the inverse spectral gap of H for that eigenstate and the cost of evolving with H for some fixed time. The goal of spectral gap amplification is to construct a Hamiltonian H' with the same eigenstate as H but a bigger spectral gap, requiring that constant-time evolutions with H' and H are implemented with nearly the same cost. We show that a quadratic spectral gap amplification is possible when H satisfies a frustration-free property and give H' for these cases. This results in quantum speedups for optimization problems. It also yields improved constructions for adiabatic simulations of quantum circuits and for the preparation of projected entangled pair states (PEPS), which play an important role in…
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