Approximating vibronic spectroscopy with imperfect quantum optics

Clements, William R.; Renema, Jelmer J.; Eckstein, Andreas; Valido, Antonio A.; Lita, Adriana E.; Gerrits, Thomas; Nam, Sae Woo; Kolthammer, W. Steven; Huh, Joonsuk

doi:10.1088/1361-6455/aaf031

Cited by 45 publications

(50 citation statements)

References 49 publications

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“…Implications for recent experiments.-Motivated by its experimental advantages, recently several small-scale GBS experiments have been demonstrated [47][48][49]. It is interesting to analyze if those experiments satisfy our simulability condition for some error threshold .…”

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confidence: 99%

Regimes of Classical Simulability for Noisy Gaussian Boson Sampling

Brod

Quesada

et al. 2020

Phys. Rev. Lett.

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As a promising candidate for exhibiting quantum computational supremacy, Gaussian boson sampling (GBS) is designed to exploit the ease of experimental preparation of Gaussian states. In this work, we establish sufficient conditions for efficient approximate simulation of GBS under the effect of errors such as photon losses and dark counts. We show that efficient simulation of GBS is possible if the per-photon transmission rate scales as the inverse of the square root of the average number of photons. As a consequence, for architectures where losses increase exponentially with circuit depth, our results place an upper bound on circuit size beyond which GBS becomes simulable. We also find that increasing the amount of input squeezing is helpful to evade our classical simulation algorithm, which suggests a potential route to fight against photon loss.

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confidence: 99%

Regimes of Classical Simulability for Noisy Gaussian Boson Sampling

Brod

Quesada

et al. 2020

Phys. Rev. Lett.

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“…The 300-node p_hat300-1 random graph has maximum known clique size of eight[78]. This figure shows three different 8-node cliques found by the GBS algorithm, which appear highlighted in red.>>> # sort cliques in decreasing size >>> cliques = sorted(cliques, key=len, reverse=True) >>> cliques[:3] # the three largest cliques [[48,53,87,152, 243, 273, 279, 295],[37,78,158, 207, 218, 239, 249, 267],[17,48,106,148, 170, 196, 224, 234]] >>> from strawberryfields.apps import plot >>> p0 = plot.graph(g, cliques[0]) # SeeFig. 7(left) >>> p1 = plot.graph(g, cliques[1]) # SeeFig.…”

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confidence: 99%

Applications of near-term photonic quantum computers: software and algorithms

Bromley

Arrazola

Jahangiri

et al. 2020

Quantum Sci. Technol.

109

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Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based problems, point processes, and molecular vibronic spectra in chemistry. The development of dedicated quantum software is a key enabler in permitting users to program devices and implement algorithms. In this work, we introduce a new applications layer for the Strawberry Fields photonic quantum computing library. The applications layer provides users with the necessary tools to design and implement algorithms using GBS with only a few lines of code. This paper serves a dual role as an introduction to the software, supported with example code, and also a review of the current state of the art in GBS algorithms.1 This document refers to Strawberry Fields version 0.12.Full documentation is available online at strawberryfields.readthedocs.io and the code is available at github.com/XanaduAI/ strawberryfields.

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“…Note that these results can also be used to determine the normalisation factors for many-particle wave functions such as (122). In that case, the state is chosen such that e o k | e o l = δ o k ,o l , such that (124) implies that…”

Section: Fermionsmentioning

confidence: 99%

Signatures of many-particle interference

Walschaers¹

2020

J. Phys. B: At. Mol. Opt. Phys.

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Quantum systems with many constituents give rise to a range of conceptual, analytical and computational challenges, hence, the label "complex systems". In the first place, one can think of interactions, described by a manybody Hamiltonian, as the source of such complexity. However, it has gradually become clear that, even in absence of interactions, many-body systems are more than just the sum of their parts. This feature is due to many-body interference.One of the most well-known interference phenomena is the Hong-Ou-Mandel effect, where total destructive interference is observed for a pair of (noninteracting) identical photons. This two-photon interference effect can be generalised to systems of many particles which can be either fermionic or bosonic. The resulting many-particle interference goes beyond quantum statistical effects that are contained in the Bose-Einstein or Fermi-Dirac distributions, and is dynamical in nature.This Tutorial will introduce the mathematical framework for describing systems of identical particles, and explain the notion of indistinguishability. We will then focus our attention on dynamical systems of free particles and formally introduce the concept of many-particle interference. Its impact on manyparticle transition probabilities is computationally challenging to evaluate, and it becomes rapidly intractable for systems with large numbers of identical particles. Hence, this Tutorial will build up towards alternative, more efficient methods for observing signatures of many-particle interference. A first type of signatures relies on the detection of a highly sensitive -but also highly fragile-processes of total destructive interference that occurs in interferometers with a high degree of symmetry. A second class of signatures is based on the statistical features that arise when we study the typical behaviour of correlations between a small number of the interferometer's output ports. We will ultimately show how these statistical signatures of many-particle interference lead us to a statistical version of the Hong-Ou-Mandel effect.The work presented in this Tutorial was one of the four shortlisted finalists of the 2018 DPG SAMOP dissertation prize.

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Approximating vibronic spectroscopy with imperfect quantum optics

Cited by 45 publications

References 49 publications

Regimes of Classical Simulability for Noisy Gaussian Boson Sampling

Regimes of Classical Simulability for Noisy Gaussian Boson Sampling

Applications of near-term photonic quantum computers: software and algorithms

Signatures of many-particle interference

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