A note on superposition of two unknown states using Deutsch CTC model

Sami, Sasha; Chakrabarty, Indranil

doi:10.1142/s0217732316501704

Cited by 8 publications

(6 citation statements)

References 57 publications

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“…Recently, it was proven that a quantum operation that adds two unknown quantum states is forbidden in general [24,25]. Since then, im-arXiv:1709.07409v2 [quant-ph] 17 Oct 2018 portant results in optimized approximate or probabilistic quantum adders have been analyzed, and in some cases implemented, which may find applications to different aspects of quantum technologies [24][25][26][27][28][29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

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Quantum autoencoders via quantum adders with genetic algorithms

Lamata

Alvarez-Rodriguez

Martín-Guerrero

et al. 2018

Quantum Sci. Technol.

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The quantum autoencoder is a recent paradigm in the field of quantum machine learning, which may enable an enhanced use of resources in quantum technologies. To this end, quantum neural networks with less nodes in the inner than in the outer layers were considered. Here, we propose a useful connection between quantum autoencoders and quantum adders, which approximately add two unknown quantum states supported in different quantum systems. Specifically, this link allows us to employ optimized approximate quantum adders, obtained with genetic algorithms, for the implementation of quantum autoencoders for a variety of initial states. Furthermore, we can also directly optimize the quantum autoencoders via genetic algorithms. Our approach opens a different path for the design of quantum autoencoders in controllable quantum platforms.

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Section: Introductionmentioning

confidence: 99%

“…In the last years, the design and implementation of approximate quantum adders [24][25][26][27][28][29][30][31][32] has emerged with unexpected connections. Recently, it was proven that a quantum operation that adds two unknown quantum states is forbidden in general [24,25].…”

Section: Introductionmentioning

confidence: 99%

Quantum autoencoders via quantum adders with genetic algorithms

Lamata

Alvarez-Rodriguez

Martín-Guerrero

et al. 2018

Quantum Sci. Technol.

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“…At the same time, a probabilistic quantum adder with partial prior knowledge of the summands was proposed [2] and has been realized in the lab [3,4]. In parallel, a study of quantum adders in the context of closed timelike curves has been developed [5]. The use of approximate quantum adders as constituents of quantum algorithms and protocols is certainly promising, as showcased in a recent result with the first application of a quantum adder [6].…”

Section: Introductionmentioning

confidence: 99%

Approximate Quantum Adders with Genetic Algorithms: An IBM Quantum Experience

Li¹,

Alvarez-Rodriguez²,

Lamata³

et al. 2017

Quantum Measurements and Quantum Metrology

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It has been proven that quantum adders are forbidden by the laws of quantum mechanics. We analyze theoretical proposals for the implementation of approximate quantum adders and optimize them by means of genetic algorithms, improving previous protocols in terms of e ciency and delity. Furthermore, we experimentally realize a suitable approximate quantum adder with the cloud quantum computing facilities provided by IBM Quantum Experience. The development of approximate quantum adders enhances the toolbox of quantum information protocols, paving the way for novel applications in quantum technologies.

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“…Additionally, recent works [28][29][30] have aimed at simulating closed timelike curves and replicating their re-sults. There has also been significant research on flow of information [31,32], causality considerations [33][34][35][36][37], no-go theorems [38], state preparation [39], and thermodynamic considerations [40] within CTCs. CTCs and entanglement [41][42][43][44] is an equally interesting avenue for research.…”

Section: Introductionmentioning

confidence: 99%

Revisiting integer factorization using closed timelike curves

Ghosh

Adhikary

Paul

2018

Quantum Inf Process

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Closed Timelike Curves are relativistically valid objects allowing time travel to the past. Treating them as computational objects opens the door to a wide range of results which cannot be achieved using non relativistic quantum mechanics. Recently, research in classical and quantum computation has focused on effectively harnessing the power of these curves. In particular, Brun (Found. Phys. Lett., 2003) has shown that CTCs can be utilized to efficiently solve problems like factoring and QSAT (Quantified Satisfiability Problem). In this paper, we find a flaw in Brun's algorithm and propose a modified algorithm to circumvent the flaw.

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A note on superposition of two unknown states using Deutsch CTC model

Cited by 8 publications

References 57 publications

Quantum autoencoders via quantum adders with genetic algorithms

Quantum autoencoders via quantum adders with genetic algorithms

Approximate Quantum Adders with Genetic Algorithms: An IBM Quantum Experience

Revisiting integer factorization using closed timelike curves

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