## Posts Tagged ‘**computation**’

## “One of the most singular characteristics of the art of deciphering is the strong conviction possessed by every person, even moderately acquainted with it, that he is able to construct a cipher which nobody else can decipher.”*…

And yet, for centuries no one has succeeded. Now, as Erica Klarreich reports, cryptographers want to know which of five possible worlds we inhabit, which will reveal whether truly secure cryptography is even possible…

Many computer scientists focus on overcoming hard computational problems. But there’s one area of computer science in which hardness is an asset: cryptography, where you want hard obstacles between your adversaries and your secrets.

Unfortunately, we don’t know whether secure cryptography truly exists. Over millennia, people have created ciphers that seemed unbreakable right until they were broken. Today, our internet transactions and state secrets are guarded by encryption methods that seem secure but could conceivably fail at any moment.

To create a truly secure (and permanent) encryption method, we need a computational problem that’s hard enough to create a provably insurmountable barrier for adversaries. We know of many computational problems that seem hard, but maybe we just haven’t been clever enough to solve them. Or maybe some of them are hard, but their hardness isn’t of a kind that lends itself to secure encryption. Fundamentally, cryptographers wonder: Is there enough hardness in the universe to make cryptography possible?

In 1995, Russell Impagliazzo of the University of California, San Diego broke down the question of hardness into a set of sub-questions that computer scientists could tackle one piece at a time. To summarize the state of knowledge in this area, he described five possible worlds — fancifully named Algorithmica, Heuristica, Pessiland, Minicrypt and Cryptomania — with ascending levels of hardness and cryptographic possibility. Any of these could be the world we live in…

Explore each of them– and their implications for secure encryption– at “Which Computational Universe Do We Live In?” from @EricaKlarreich in @QuantaMagazine.

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**As we contemplate codes,** we might we might send communicative birthday greetings to a frequently–featured hero of your correspondent, Claude Elwood Shannon; he was born on this date in 1916. A mathematician, electrical engineer– and cryptographer– he is known as “the father of information theory.” But he is also remembered for his contributions to digital circuit design theory and for his cryptanalysis work during World War II, both as a codebreaker and as a designer of secure communications systems.

## “Visualization gives you answers to questions you didn’t know you had”*…

Physical representations of data have existed for thousands of years. The List of Physical Visualizations (and the accompanying Gallery) collect illustrative examples, e.g…

5500 BC – Mesopotamian Clay Tokens

The earliest data visualizations were likely physical: built by arranging stones or pebbles, and later, clay tokens. According to an eminent archaeologist (Schmandt-Besserat, 1999):

“Whereas words consist of immaterial sounds, the tokens were concrete, solid, tangible artifacts, which could be handled, arranged and rearranged at will. For instance, the tokens could be ordered in special columns according to types of merchandise, entries and expenditures; donors or recipients. The token system thus encouraged manipulating data by abstracting all possible variables. (Harth 1983. 19) […] No doubt patterning, the presentation of data in a particular configuration, was developed to highlight special items (Luria 1976. 20).”Clay tokens suggest that physical objects were used to externalize information, support visual thinking and enhance cognition way before paper and writing were invented…

There are 370 entries (so far). Browse them at List of Physical Visualizations (@dataphys)

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**As we celebrate the concrete,** we might carefully-calculated birthday greetings to Rolf Landauer; he was born on this date in 1927. A physicist, he made a number important contributions in a range of areas: the thermodynamics of information processing, condensed matter physics, and the conductivity of disordered media.

He is probably best remembered for “Landauer’s Principle,” which described the energy used during a computer’s operation. Whenever the machine is resetting for another computation, bits are flushed from the computer’s memory, and in that electronic operation, a certain amount of energy is lost (a simple logical consequence of the second law of thermodynamics). Thus, when information is erased, there is an inevitable “thermodynamic cost of forgetting,” which governs the development of more energy-efficient computers. The maximum entropy of a bounded physical system is finite– so while most engineers dealt with practical limitations of compacting ever more circuitry onto tiny chips, Landauer considered the theoretical limit: if technology improved indefinitely, how soon will it run into the insuperable barriers set by nature?

A so-called logically reversible computation, in which no information is erased, may in principle be carried out without releasing any heat. This has led to considerable interest in the study of reversible computing. Indeed, without reversible computing, increases in the number of computations per joule of energy dissipated must eventually come to a halt. If Koomey‘s law continues to hold, the limit implied by Landauer’s principle would be reached around the year 2050.

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