Artificial intelligence has allowed scientists to make significant progress in cracking a mysterious ancient text, the meaning of which has eluded scholars for centuries.
DNA as a data storage medium has several advantages, including far greater data density compared to electronic media. We propose that schemes for data storage in the DNA of living organisms may benefit from studying the reconstruction problem, which is applicable whenever multiple reads of noisy data are available. This strategy is uniquely suited to the medium, which inherently replicates stored data in multiple distinct ways, caused by mutations. We consider noise introduced solely by uniform tandem-duplication, and utilize the relation to constant-weight integer codes in the Manhattan metric. By bounding the intersection of the cross-polytope with hyperplanes, we prove the existence of reconstruction codes with greater capacity than known error-correcting codes, which we can determine analytically for any set of parameters.
My ten hour white noise video now has five copyright claims! 🙂 pic.twitter.com/dX9PCM1qGx
— Sebastian Tomczak (@littlescale) January 4, 2018
Information Theory and signal processing FTW!
(Aside: This is a great example of how people really don’t understand our copyright system or science in general.)
This paper answers Bell’s question: What does quantum information refer to? It is about quantum properties represented by subspaces of the quantum Hilbert space, or their projectors, to which standard (Kolmogorov) probabilities can be assigned by using a projective decomposition of the identity (PDI or framework) as a quantum sample space. The single framework rule of consistent histories prevents paradoxes or contradictions. When only one framework is employed, classical (Shannon) information theory can be imported unchanged into the quantum domain. A particular case is the macroscopic world of classical physics whose quantum description needs only a single quasiclassical framework. Nontrivial issues unique to quantum information, those with no classical analog, arise when aspects of two or more incompatible frameworks are compared.
This article belongs to the Special Issue Quantum Information and Foundations
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All living things are made of cells, and all cells are powered by electrochemical charges across thin lipid membranes — the ‘proton motive force.’ We know how these electrical charges are generated by protein machines at virtually atomic resolution, but we know very little about how membrane bioenergetics first arose. By tracking back cellular evolution to the last universal common ancestor and beyond, scientist Nick Lane argues that geologically sustained electrochemical charges across semiconducting barriers were central to both energy flow and the formation of new organic matter — growth — at the very origin of life. Dr. Lane is a professor of evolutionary biochemistry in the Department of Genetics, Evolution and Environment at University College London. His research focuses on how energy flow constrains evolution from the origin of life to the traits of complex multicellular organisms. He is a co-director of the new Centre for Life’s Origins and Evolution (CLOE) at UCL, and author of four celebrated books on life’s origins and evolution. His work has been recognized by the Biochemical Society Award in 2015 and the Royal Society Michael Faraday Prize in 2016.
Roughly speaking, an ergodic system is one that mixes well. You get the same result whether you average its values over time or over space. This morning I ran across the etymology of the word ergodic.
As the ultimate information processing device, the brain naturally lends itself to be studied with information theory. Application of information theory to neuroscience has spurred the development of principled theories of brain function, has led to advances in the study of consciousness, and to the development of analytical techniques to crack the neural code, that is to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative test of hypotheses about how the brain encodes and transmits across areas the information used for specific functions. This Special Issue emphasizes contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience. Research work at the interface of neuroscience, Information Theory and other disciplines is also welcome. A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory". Deadline for manuscript submissions: 1 December 2017
The ‘creator’ of Bitcoin, Satoshi Nakamoto, is the world’s most elusive billionaire. Very few people outside of the Department of Homeland Security know Satoshi’s real name. In fact, DHS will not publicly confirm that even THEY know the billionaire’s identity. Satoshi has taken great care to keep his identity secret employing the latest encryption and obfuscation methods in his communications. Despite these efforts (according to my source at the DHS) Satoshi Nakamoto gave investigators the only tool they needed to find him — his own words. Using stylometry one is able to compare texts to determine authorship of a particular work. Throughout the years Satoshi wrote thousands of posts and emails and most of which are publicly available. According to my source, the NSA was able to the use the ‘writer invariant’ method of stylometry to compare Satoshi’s ‘known’ writings with trillions of writing samples from people across the globe. By taking Satoshi’s texts and finding the 50 most common words, the NSA was able to break down his text into 5,000 word chunks and analyse each to find the frequency of those 50 words. This would result in a unique 50-number identifier for each chunk. The NSA then placed each of these numbers into a 50-dimensional space and flatten them into a plane using principal components analysis. The result is a ‘fingerprint’ for anything written by Satoshi that could easily be compared to any other writing.
Significance A qualitatively more diverse range of possible behaviors emerge in many-particle systems once external drives are allowed to push the system far from equilibrium; nonetheless, general thermodynamic principles governing nonequilibrium pattern formation and self-assembly have remained elusive, despite intense interest from researchers across disciplines. Here, we use the example of a randomly wired driven chemical reaction network to identify a key thermodynamic feature of a complex, driven system that characterizes the “specialness” of its dynamical attractor behavior. We show that the network’s fixed points are biased toward the extremization of external forcing, causing them to become kinetically stabilized in rare corners of chemical space that are either atypically weakly or strongly coupled to external environmental drives. Abstract A chemical mixture that continually absorbs work from its environment may exhibit steady-state chemical concentrations that deviate from their equilibrium values. Such behavior is particularly interesting in a scenario where the environmental work sources are relatively difficult to access, so that only the proper orchestration of many distinct catalytic actors can power the dissipative flux required to maintain a stable, far-from-equilibrium steady state. In this article, we study the dynamics of an in silico chemical network with random connectivity in an environment that makes strong thermodynamic forcing available only to rare combinations of chemical concentrations. We find that the long-time dynamics of such systems are biased toward states that exhibit a fine-tuned extremization of environmental forcing.
Take chemistry, add energy, get life. The first tests of Jeremy England’s provocative origin-of-life hypothesis are in, and they appear to show how order can arise from nothing.
The situation changed in the late 1990s, when the physicists Gavin Crooks and Chris Jarzynski derived “fluctuation theorems” that can be used to quantify how much more often certain physical processes happen than reverse processes. These theorems allow researchers to study how systems evolve — even far from equilibrium.
I want to take a look at these papers as well as several about which the article is directly about.
Any claims that it has to do with biology or the origins of life, he added, are “pure and shameless speculations.”
Some truly harsh words from his former supervisor? Wow!
maybe there’s more that you can get for free
Most of what’s here in this article (and likely in the underlying papers) sounds to me to have been heavily influenced by the writings of W. Loewenstein and S. Kauffman. They’ve laid out some models/ideas that need more rigorous testing and work, and this seems like a reasonable start to the process. The “get for free” phrase itself is very S. Kauffman in my mind. I’m curious how many times it appears in his work?
14-16 May 2018; Auditorium Enric Casassas, Faculty of Chemistry, University of Barcelona, Barcelona, Spain
One of the most frequently used scientific words, is the word “Entropy”. The reason is that it is related to two main scientific domains: physics and information theory. Its origin goes back to the start of physics (thermodynamics), but since Shannon, it has become related to information theory. This conference is an opportunity to bring researchers of these two communities together and create a synergy. The main topics and sessions of the conference cover:
- Physics: classical Thermodynamics and Quantum
- Statistical physics and Bayesian computation
- Geometrical science of information, topology and metrics
- Maximum entropy principle and inference
- Kullback and Bayes or information theory and Bayesian inference
- Entropy in action (applications)
The inter-disciplinary nature of contributions from both theoretical and applied perspectives are very welcome, including papers addressing conceptual and methodological developments, as well as new applications of entropy and information theory.
All accepted papers will be published in the proceedings of the conference. A selection of invited and contributed talks presented during the conference will be invited to submit an extended version of their paper for a special issue of the open access Journal Entropy.
Songs about communication, telephones, conversation, satellites, love, auto-tune and even one about a typewriter! They all relate at least tangentially to the topic at hand. To up the ante, everyone should realize that digital music would be impossible without Shannon’s seminal work.
Let me know in the comments or by replying to one of the syndicated copies listed below if there are any great tunes that the list is missing.
Enjoy the list and the book!
Jimmy Soni and Rob Goodman wrote the first biography of the digital pioneer
Knowing that I’ve read a lot about Shannon and even Vannevar Bush over the years, I’m pleasantly surprised to read some interesting tidbits about them that I’ve not previously come across. I was a bit worried that this text wouldn’t provide me with much or anything new on the subjects at hand.
I’m really appreciating some of the prose and writing structure, particularly given that it’s a collaborative work between two authors. At times there are some really nonstandard sentence structures, but they’re wonderful in their rule breaking.
They’re doing an excellent job so far of explaining the more difficult pieces of science relating to information theory. In fact, some of the intro was as good as I think I’ve ever seen simple explanations of what is going on within the topic. I’m also pleased that they’ve made some interesting forays into topics like eugenics and the background role it played in the story for Shannon.
They had a chance to do a broader view of the history of computing, but opted against it, or at least must have made a conscious choice to leave out Babbage/Lovelace within the greater pantheon. I can see narratively why they may have done this knowing what is to come later in the text, but a few sentences as a nod would have been welcome.
The book does, however, get on my nerves with one of my personal pet peeves in popular science and biographical works like this: while there are reasonable notes at the end, absolutely no proper footnotes appear at the bottoms of pages or even indicators within the text other than pieces of text with quotation marks. I’m glad the notes even exist in the back, but it just drives me crazy that publishers blatantly hide them this way. The text could at least have had markers indicating where to find the notes. What are we? Animals?
Nota bene: I’m currently reading an advanced reader copy of this; the book won’t be out until mid-July 2017.
Instagram filter used: Clarendon
Photo taken at: Gerrish Swim & Tennis Club
