Boson sampling for molecular vibronic spectra

By Joonsuk Huh, Gian Giacomo Guerreschi, B. Peropadre, Jarrod R. McClean, A. Aspuru‐Guzik. Nature Photonics, 2014

344 citations recorded by the source corpus.

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. A quantum simulation scheme is proposed for molecular vibronic spectra, a problem for which no efficient classical algorithm is currently known. The simulation is efficiently performed on a boson sampling machine simply by modifying the input state.

Subfields: Artificial Intelligence, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/1c7af87b0e3b24e3229aa7d04918e5519884682e

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Citations in the corpus

Classical boson sampling algorithms with superior performance to near-term experiments (2017, methodology): “We are hopeful that the techniques we have presented in this paper can be carried over to Gaussian boson sampling, potentially allowing for the classical simulation of experiments designed to generate molecular vibronic spectra [60].”
A fully programmable 100-spin coherent Ising machine with all-to-all connections (2016, background): “A proposal for a boson-sampling-like experiment using squeezed states (57) also motivates work on multiplexed OPO systems, which can produce squeezed states (58).”
Quantum algorithms: an overview (2015, neutral): “Table only includes some \largest" problem instances solved thus far. mind, subsequent work has explored connections to molecular vibrations and vibronic spectra [50, 67].”
Materials challenges and opportunities for quantum computing hardware (2021, methodology): “Other demonstrations include implementing quantum approximate optimization algorithms on trapped-ion processors (9) and using bosonic modes to perform calculations that are computationally hard, such as calculating the vibronic spectra of small molecules by using the bosonicmodes of microwave caviti”
Large-scale quantum photonic circuits in silicon (2016, background): “As Boson Sampling [20, 21] does not feed-forward or error correction, it promises a near-term win of a quantum system over classical machines [22], but still requires hundreds of spatial modes [23–26].”
Circuit-centric quantum classifiers (2018, background): “[4] Joonsuk Huh, Gian Giacomo Guerreschi, Borja Peropadre, Jarrod R McClean, and Alán Aspuru-Guzik.”
Integrated photonic quantum technologies (2019, positive): “approximate eigenvalues for both ground and excited states [113]. Moreover, a modification of Boson sampling allows molecular vibrionic spectra to be calculated with the inclusion of squeezed photons [114], and an alternative scheme was proposed and realised in a universal linear-optic device (Fig.5”
Quantum computational advantage using photons (2020, background): “…quantum computational advantage, the GBS links to several potentially practical applications including certifiable random numbers, graph optimization ( 32-34 ), graph similarity ( 35 ), point process ( 36 ), molecular docking ( 37), quantum chemistry ( 38,39 ), and quantum machine learning ( 64 ).”
Quantum circuits with many photons on a programmable nanophotonic chip (2021, methodology): “In the photonic algorithm, optical modes represent the vibrational normal modes of the molecule and the device is programmed in terms of squeezing, displacement, and linear interferometers to efficiently generate Franck-Condon profiles [12, 43].”
Efficient Multiphoton Sampling of Molecular Vibronic Spectra on a Superconducting Bosonic Processor (2019, methodology): “The modification of the creation and annihilation operators under the mode transformation is given in [16]”