Tracking the flow of quantum information

In recent times researchers have discovered a formula to understand where quantum objects when they are transmitted. With this formula researchers may be able to have better control over quantum computing. This formula was discovered at Yale and helpt to control open quantum systems in many different situations. The researchers can control quantum objects with the model of rain and a gutter. The gutter and the gates within the gutter are meant to represent dissiapation. Usually quantum objects get destroyed in this process, as they are too fragile, but ocassionally the objects can be desgned to be robust enough to control and protect agaisnt this. The formula the researchers created showed that there is a situation where one superposition is not possible. Professor Amber Jiang describes it as "In other words, such a superposition state always loses some of its quantum properties as the 'droplet' flows completely into both puddles."

I found this aritcle interesting as I think that it is important that we understand what we are working with. In this case I think finding a deeper understanding of quantum objects is important if researchers intend to keep exploring the world of quantum computing. I also thought it was cool how the researchers compared their formual to an understandable model. I think that it is very helpful to undertanding computer science when the idea is compared to a real life scenario.

1. Victor V. Albert, Barry Bradlyn, Martin Fraas, Liang Jiang. Geometry and Response of Lindbladians. Physical Review X, 2016; 6 (4) DOI: 10.1103/PhysRevX.6.041031

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  • Quantum entanglement
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Supercomputers Capture the Crush in Biological Cells

In recent times researchers have been trying to simulate biology within computers. Michigan State University researcher Michael Feig has been able to understand how protiens are affected by real enviroments through computer models. To do this Michael used one of the world's most powerful computers, located in Japan. According to Micahel his team has, "'revealed unprecedented details about what exactly takes place inside biological cells, and how proteins in particular behave in their natural environment.'" The research began with the question of whether the crowding of biolgical cells has affects on a biological cell's ability to carry out functions. By using the K computer, located in Kobe Japan, Michael and his team ran simulations of the interior of bacterium. These models revealed that proteins may not be as stable in dense enviorments. This is because they lose the structures necessary to carry out their biological function. On the other hand the density brings all of the biological processes closer together causing a more efficeincy in creating energy. Fieg says this is just the beginning of a complete cell simulation. 

I found this article intersting as I think that it is really cool that it is possible to model biology on a computer. Typically in biology to study processes or cells one would have to look into a microscope or perform experiemnts and wait for the results. By using a model on a computer one can simply zoom in and out of any situation one wants at any time. Also to think that eventualy we will be to be able to model whole cells, and maybe oneday even be able to model a whole organism would be really cool. Instead of testing vaccines on animals we could simply use the models to test new medicines and vaccines. 

Michigan State University. "Supercomputers capture the crush in biological cells." ScienceDaily. ScienceDaily, 2 November 2016. <www.sciencedaily.com/releases/2016/11/161102143803.htm>.

Making Computers Explain Themselves

In todays world many forms of technolgy have some form of artificial intelligence. A common form of artificial intelligence is Google's assitant or Apple's Siri which are commonly found on most smart phones. Although the artificial intelligence we carry seems quite refined there is still more research being done. Current artificial intelligence looks for patterns within data to make predictions and infer about ceratin topics. This is known as a neural net. Although researchers recognize that the neural net is how artificial intelligence is making the predictions they are still unsure as how the neural net classifies data. Researchers at MIT are planning to present a new way to show not only the predictions of the neural net, but also the rational behind the artificial intelligence decisions at the Association for Computational Linguistics' Conference on Emperical Methonds in Natural Language Processing. Because researchers have not been able to show how the artificial intelligence learns things, doctors tend not to trust machines that use artificial intelligence. The neural net or neural network is referenced as neural because its structure resembles that of a brain. The network is made of processing nodes, each capable of computing simple computations.

I found this article intersting as I found it quite fascinating that artificial intelligence has been created and already been put out for consumer use, yet researchers are still unclear as to how the system classifies its data. The idea that something is not completely understood, yet it has been put out for use of the masses is  a little absurd in my opinion. I also thought that the idea of a neural network resembling the structure of a brain was quite cool. To think that in technology there is also a "brain" is pretty cool.

Larry Hardesty | MIT News Office. "Making Computers Explain Themselves." MIT News. N.p., 27 Oct. 2016. Web. 05 Nov. 2016.

http://news.mit.edu/2016/making-computers-explain-themselves-machine-learning-1028