TJ
T.G. Jacobs
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Quantum Communication Complexity on Near-Term Networks
Solving the Equality Problem with Realistic Noise
Quantum computers allow us to solve certain problems that are unsolvable using classical computers. In this study we focus on solving the equality problem by simulating a three quantum computer network and using the communication complexity to determine if our theoretical quantum advantage is still there in practice. We want to know how the noise from realistic quantum networks that already exist affect this communication complexity. We found that we can beat the classical solution when simulating a laboratory setup in which the quantum computers are in close proximity to each other and when using only a small bit strings. However, when moving to setups in which there are kilometres between quantum computers instead of metres or when using larger bit strings as input to our problem we see that the noise becomes too much to simulate.
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Quantum computers allow us to solve certain problems that are unsolvable using classical computers. In this study we focus on solving the equality problem by simulating a three quantum computer network and using the communication complexity to determine if our theoretical quantum advantage is still there in practice. We want to know how the noise from realistic quantum networks that already exist affect this communication complexity. We found that we can beat the classical solution when simulating a laboratory setup in which the quantum computers are in close proximity to each other and when using only a small bit strings. However, when moving to setups in which there are kilometres between quantum computers instead of metres or when using larger bit strings as input to our problem we see that the noise becomes too much to simulate.
in bio-informatics visualisations are often used to relay the results of genome-wide association studies (GWAS), which can be used to get a better inside into the genetics of diseases. Over the years many websites have been developed, which can create visualisations for a variety of GWAS, with one of the most famous being locuszoom. Recent advancements in technology have allowed for collection of data which wasn't previously possible and which no visualisation tool currently supports. For the first time it is now possible to collect data on the interactions between two different types of genetic mutations: Single Nucleotide Polymorphisms, which consist of a single change in one nucleotide (one letter in a string of DNA) and Structural Variants, which consist of a change in a series of nucleotides. This paper builds upon an already existing visualisation tool snpxplorer and the goal is to design a visualisation, which captures thesse interactions and to add a new, easily integratable section to snpxplorer containing this new visualisation.
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in bio-informatics visualisations are often used to relay the results of genome-wide association studies (GWAS), which can be used to get a better inside into the genetics of diseases. Over the years many websites have been developed, which can create visualisations for a variety of GWAS, with one of the most famous being locuszoom. Recent advancements in technology have allowed for collection of data which wasn't previously possible and which no visualisation tool currently supports. For the first time it is now possible to collect data on the interactions between two different types of genetic mutations: Single Nucleotide Polymorphisms, which consist of a single change in one nucleotide (one letter in a string of DNA) and Structural Variants, which consist of a change in a series of nucleotides. This paper builds upon an already existing visualisation tool snpxplorer and the goal is to design a visualisation, which captures thesse interactions and to add a new, easily integratable section to snpxplorer containing this new visualisation.