Cryptography in Quantum Computing

Choy, Pam; Cates, Dustin; Chehwan, Florent; Rodríguez, Cindy Mariana Ariza; Leider, Avery; Tappert, Charles C.

doi:10.1007/978-3-030-32520-6_30

Cited by 2 publications

(1 citation statement)

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“…At the same time, quantum computing has emerged as another important pillar in modern research attracting the attention of many researchers due to its potential to execute certain tasks with an exponentially reduced amount of resources both in time and space compared to classical processors [7]. It has already shown promising results in various fields, such as optimization [8,9] and cryptography [10].…”

Section: Introductionmentioning

confidence: 99%

Dual-Parameterized Quantum Circuit GAN Model in High Energy Physics

Chang

Herbert

Vallecorsa³

et al. 2021

EPJ Web Conf.

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Generative models, and Generative Adversarial Networks (GAN) in particular, are being studied as possible alternatives to Monte Carlo simulations. It has been proposed that, in certain circumstances, simulation using GANs can be sped-up by using quantum GANs (qGANs). We present a new design of qGAN, the dual-Parameterized Quantum Circuit (PQC) GAN, which consists of a classical discriminator and two quantum generators which take the form of PQCs. The first PQC learns a probability distribution over N-pixel images, while the second generates normalized pixel intensities of an individual image for each PQC input. With a view to HEP applications, we evaluated the dual-PQC architecture on the task of imitating calorimeter outputs, translated into pixelated images. The results demonstrate that the model can reproduce a fixed number of images with a reduced size as well as their probability distribution and we anticipate it should allow us to scale up to real calorimeter outputs.

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Section: Introductionmentioning

confidence: 99%