Person:

Guerreschi, Gian Giacomo

Adiabatic quantum optimization is a procedure to solve a vast class of optimization problems by slowly changing the Hamiltonian of a quantum system. The evolution time necessary for the algorithm to be successful scales inversely with the minimum energy gap encountered during the dynamics. Unfortunately, the direct calculation of the gap is strongly limited by the exponential growth in the dimensionality of the Hilbert space associated to the quantum system. Although many special-purpose methods have been devised to reduce the effective dimensionality, they are strongly limited to particular classes of problems with evident symmetries. Moreover, little is known about the computational power of adiabatic quantum optimizers in real-world conditions. Here we propose and implement a general purposes reduction method that does not rely on any explicit symmetry and which requires, under certain general conditions, only a polynomial amount of classical resources. Thanks to this method, we are able to analyze the performance of “nonideal” quantum adiabatic optimizers to solve the well-known Grover problem, namely the search of target entries in an unsorted database, in the presence of discrete local defects. In this case, we show that adiabatic quantum optimization, even if affected by random noise, is still potentially faster than any classical algorithm.

Controllable quantum devices open novel directions to both quantum computation and quantum simulation. Recently, a problem known as boson sampling has been shown to provide a pathway for solving a computationally intractable problem without the need for a full quantum computer, instead using a linear optics quantum set-up. In this work, we propose a modification of boson sampling for the purpose of quantum simulation. In particular, we show that, by means of squeezed states of light coupled to a boson sampling optical network, one can generate molecular vibronic spectra, a problem for which no efficient classical algorithm is currently known. We provide a general framework for carrying out these simulations via unitary quantum optical transformations and supply specific molecular examples for future experimental realization.