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Quantum simulation uses a well-known quantum system to predict the behavior of another quantum system. Certain limitations in this technique arise, however, when applied to specific problems, as we demonstrate with a theoretical and experimental study of an algorithm to find the low-lying spectrum of a Hamiltonian. While the number of elementary quantum gates does scale polynomially with the size of the system, it increases inversely to the desired error bound $epsilon$. Making such simulations robust to decoherence using fault-tolerance constructs requires an additional factor of $1/ epsilon$ gates. These constraints are illustrated by using a three qubit nuclear magnetic resonance system to simulate a pairing Hamiltonian, following the algorithm proposed by Wu, Byrd, and Lidar.
Four-body interaction plays an important role in many-body systems, and it can exhibit interesting phase transition behaviors. Historically it was the need to efficiently simulate quantum systems that lead the idea of a quantum computer. In this Lett
Liquid crystals offer several advantages as solvents for molecules used for nuclear magnetic resonance quantum computing (NMRQC). The dipolar coupling between nuclear spins manifest in the NMR spectra of molecules oriented by a liquid crystal permits
The number of steps any classical computer requires in order to find the prime factors of an $l$-digit integer $N$ increases exponentially with $l$, at least using algorithms known at present. Factoring large integers is therefore conjectured to be i
Hamiltonian simulation is one of the most important problems in quantum computation, and quantum singular value transformation (QSVT) is an efficient way to simulate a general class of Hamiltonians. However, the QSVT circuit typically involves multip
We present an open-source software for the simulation of observables in nuclear magnetic/quadrupole resonance experiments (NMR/NQR) on solid-state samples, developed to assist experimental research in the design of new strategies for the investigatio