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  • mazsa 10:12 on February 12, 2012 Permalink | Reply
    Tags: , , Mathematics   

    Markets are efficient iff P = NP http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1773169

    Cf. http://www.claymath.org/millennium/P_vs_NP/

    http://www.eecs.harvard.edu/econcs/pubs/ec270-chen.pdf

    http://www.constrainedblisspoint.com/tag/fermats-last-theorem/

    http://www.aleph.se/andart/archives/2011/08/if_computer_scientists_are_right_you_can_make_money_on_the_market_if_economists_are_right_you_can_compute_fast.html

    http://rjlipton.wordpress.com/2011/08/11/deolalikars-claim-one-year-later/#comment-12862

    http://news.ycombinator.com/item?id=2895474

    http://news.ycombinator.com/item?id=1144548

    http://www.reddit.com/r/Economics/comments/b1w3n/markets_are_efficient_if_and_only_if_p_np_and_he/

     
  • mazsa 11:56 on December 6, 2011 Permalink | Reply
    Tags: , , Mathematics, , ,   

    “And yet, even though useful quantum computers might still be decades away, many of their payoffs are already arriving. For example, the mere possibility of quantum computers has all but overthrown a conception of the universe that scientists like Stephen Wolfram have championed. That conception holds that, as in the “Matrix” movies, the universe itself is basically a giant computer, twiddling an array of 1’s and 0’s in essentially the same way any desktop PC does.

    Quantum computing has challenged that vision by showing that if “the universe is a computer,” then even at a hard-nosed theoretical level, it’s a vastly more powerful kind of computer than any yet constructed by humankind. Indeed, the only ways to evade that conclusion seem even crazier than quantum computing itself: One would have to overturn quantum mechanics, or else find a fast way to simulate quantum mechanics using today’s computers.” http://www.nytimes.com/2011/12/06/science/scott-aaronson-quantum-computing-promises-new-insights.html?_r=1&ref=science&pagewanted=all

    “Carson Chow Says:
    Comment #2 December 5th, 2011 at 10:35 pm
    Nice article but I am confused about this paragraph:

    “For example, the mere possibility of quantum computers has all but overthrown a conception of the universe that scientists like Stephen Wolfram have championed. That conception holds that, as in the “Matrix” movies, the universe itself is basically a giant computer, twiddling an array of 1’s and 0’s in essentially the same way any desktop PC does.”

    A quantum universe or a classical universe are both computable aren’t they? It’s just that the quantum universe is exponentially “bigger”. In principle, you could have a classical computer just chug away painfully slowly and simulate the quantum universe, no? There is nothing in the “Matrix” universe that says the computation must be efficient is there? There are still just a countable number of possible quantum universes right?”

    “Scott Says:
    Comment #5 December 5th, 2011 at 10:59 pm
    Carson #2: Yes, as the tagline of my blog says, quantum computers can be simulated classically but with exponential slowdown.

    What we learn from quantum computing is that, if both quantum mechanics and the prevailing conjectures in complexity theory are valid, then the physical universe can’t be feasibly simulated by a computer that “twiddles an array of 1’s and 0’s in essentially the same way any desktop PC does.”

    (That last clause was meant to indicate that I was talking about efficient simulation by conventional computers — i.e., the Extended Church-Turing Thesis, or what Wikipedia calls the Feasibility Thesis. I wish I knew how to put the point more clearly within the constraints of this article, since you’re right that it might be misinterpreted!)

    For what it’s worth, Stephen Wolfram, Ed Fredkin, and other believers in “digital physics,” have been very explicit in saying that they think the universe is a classical cellular automaton—basically, a three-dimensional array of pixels—and that their view would preclude exponential speedups from quantum computation. (Wolfram believes that quantum mechanics is wrong, whereas Fredkin believes that quantum mechanics can be efficiently simulated classically.) So, these viewpoints would indeed be ruled out under the assumptions I mentioned above.

    A last remark: the Matrix movies aren’t very clear about what type of computer is being used, other than that it’s powered by human bodies! But since they never mention anything about quantum computing, and since the simulation clearly isn’t astronomically slow, it seems reasonable to assume that Keanu Reeves was trapped in some sort of classical simulation. So maybe he could’ve caused the simulation to crash by building a quantum computer and trying to run Shor’s factoring algorithm! For the version where Keanu is trapped in a quantum computation, we might need to wait for the followup trilogy, “The Unitary Matrix” (har, har).”

    “Jiav Says:
    Comment #8 December 6th, 2011 at 12:59 am
    Nice essay Scott, but how could we know our simulation is not astronomically slow?

    I’m curious to see if Greg Egan will comment this one :)

    http://www.scottaaronson.com/blog/?p=871

    Cf. http://theunitedpersons.org/blog/if-the-answer-is-42-what-is-the-question

     
  • mazsa 13:56 on June 7, 2011 Permalink | Reply
    Tags: , , , Mathematics,   

    INFORMATION AND ITS METRIC “When one speaks of information one refers to that entity shared by all sources that are equivalent up to recoding. This observation suggests a definition of information. Information of the source S is the equivalence class of all recodings of the symbol sequences from S. This is noteworthy since information generally is left undefined in information theory. Information theory only considers the amount of information or rates of production, loss, and transmission, as measured by various entropies. [...]

    Recoding R partitions the space I of unique information sources into mutually disjoint subsets. [...]

    This suggests the definition of the more abstract information space I [...] as the set of equivalence classes of I under recodings R. [...] Elements of shall be denoted X, Y, and so on. [...] The elements of I shall be the objects of interest in the following. The necessary logical distinction between the class X and its constituent sources will be blurred in the following. A reference to X as an information source should be construed as connoting the common properties of its members. As a source, X is the generic source. We can speak, in a similar vein, of the events or measurements of source X. [...]

    Theorem: d is a metric and (I, d) is a metric space. [...]

    The theorem indicates that the space of information sources has quite a bit of topological structure. For example, the notion of [epsilon]-balls of “close” information sources, the continuity of functions on information sources, and the limits and convergence of sequences of information sources, can be developed. These and numerical computations of information distances will follow in a sequel. [...]

    CONCLUDING REMARKS

    One question that arises in this development is why not simply use mutual information instead of the information metric. Aside from the pseudo-geometric picture we have presented, we note that the former measures only a kind of informational correlation. The information metric, however, quantifies the degree of recoding equivalence. And so, it provides some insight into the nature of information itself. Mutual information is a derivative concept that simply reflects the properties Shannon entropy and no more.

    The foregoing mathematical development instantiates a particular philosophical view- point, that of phenomenology. All that an observer has to work with in developing an understanding of the world are finite measurements and the attendant information. This intrinsic finiteness derives first and foremost from the limited computation resources available to an observer in a finite space-time region. The information space, as developed here, is the substrate for all perception, quantification, and modeling building. This is then structured with the pseudo-geometry as we have just shown. Only under suitable restrictions is one justified in using observations to form probabilities via (say) frequencies of events.

    Information theory was founded on a quantitative measure of the amount of information. The foregoing has given a formal definition of information itself in terms of the equivalence class structure of sources. But what of the “meaning” of this information? A motivation of this work, unstated until this point, was the conviction that an understanding of the topological structure of the metric lattice of inferential logic is necessary for developing a quantitative measure of meaning and of context. Thus, we offer no immediate answer to the question, only the hope that progress can be made. We shall return to this question in the future.”

    @inproceedings{crutchfield1990information,
    title={Information and Its Metric},
    author={Crutchfield, JP},
    booktitle={Nonlinear structures in physical systems: pattern formation, chaos, and waves: proceedings of the Second Woodward Conference, San Jose State University, November 17-18, 1989},
    pages={119},
    year={1990},
    organization={Springer}
    }

    Download: http://scholar.google.com/scholar?cluster=2410770660010935934

     
  • mazsa 19:06 on May 15, 2011 Permalink | Reply
    Tags: Mathematics   

    PROPERTY THEORY: AN INTRODUCTION

    “Property theory”, as I call it, refers to a theme – the centrality of properties, and to the
    tools and formalisms that I have evolved around that theme. These tools, that I originally developed to
    get a better understanding of some areas of mathematics, have taken a life of their own. In this article,
    I describe my development of the theory as I have developed. The purpose is both to explain the theory
    and to collect feedback about its importance, understand its relation with existing frameworks and get
    ideas on how to develop it further.

    http://www.cmi.ac.in/~vipul/propertytheory/abstractpt/introtoabstractpt.pdf

    http://www.cmi.ac.in/~vipul/propertytheory/

     
  • mazsa 06:54 on May 10, 2011 Permalink | Reply
    Tags: Mathematics   

    We propose a demonstration of Fermat’s Last Theorem using a technique certainly within the reach of Fermat himself, and then we infer that this is the marvelous proof that Fermat claimed to have. An original procedure to find all the infinite Pythagorean triples will emerge spontaneously, too. http://arxiv.org/abs/1105.0669

     
  • mazsa 20:06 on March 30, 2011 Permalink | Reply
    Tags: Mathematics, ,   

    Wolfram on the strategic direction of Mathematica: Large-Scale Systems Modeling http://blog.wolfram.com/2011/03/30/launching-a-new-era-in-large-scale-systems-modeling/

     
  • mazsa 07:28 on March 6, 2011 Permalink | Reply
    Tags: Mathematics   

    Visualizing Bayesian Inference: “What does Bayes Theorem look like? I do not mean what does the formula look like [...] I mean, how can we visualize the cognitive content of the theorem? What picture can we appeal to with the hope that any person curious about the theorem may look at it, and, after a bit of study say, “Why, that is clear—I can indeed see what is happening!” [...]” http://chance.amstat.org/2011/02/galton/

     
  • mazsa 10:18 on March 1, 2011 Permalink | Reply
    Tags: , Mathematics, ,   

    The Utility of Mathematics: “This essay discusses the best current understanding of the relationship between mathematical and empirical knowledge. It focuses on two questions:

    • Does mathematics have some sort of deep metaphysical connection with reality, and
    • if not, why is it that mathematical abstractions seem so often to be so powerfully predictive in the real world?” http://www.catb.org/~esr/writings/utility-of-math/
     
  • mazsa 11:40 on January 28, 2011 Permalink | Reply
    Tags: , , Mathematics,   

    World’s first mathematically proven hack-free software: http://www.hindustantimes.com/World-s-first-hack-free-software-developed/H1-Article1-655632.aspx

     
  • mazsa 14:23 on December 19, 2010 Permalink | Reply
    Tags: , , , Mathematics, ,   

    Why DRM will win and you can’t do anything to stop it: “Eventually your movies will play themselves once and self-destruct and you’ll be left with only the analog hole to get your gay pr0ns. Homomorphic encryption algorithms allow the secret evaluation of arbitrary logical circuits. In short this means that one can compute a useful function without knowing what either the encrypted inputs or outputs are, but whoever holds the decryption key can recover both. You can finally send your data off into the cloud and have it processed securely, or you can write the next Morris worm that no one will be able to fully reverse engineer. Of course, this also means that the next Sony rootkit you install on your computer via your Elton John CD will be invincible to analysis and your debugger will be about as useful as a punch card reader.

    [How: https://www.kuro5hin.org/story/2010/12/15/151617/78 ]

    A side effect of this ability of homomorphic encryption should allow the emulation of secure input and output with a universal turing machine constructed of homomorphic logical circuits by securely encrypting the inputs and decrypting the outputs, perhaps by mapping IO to special positions on the tape. Implementation of standard computer architectures in logic circuits would also be possible, and probably more useful than basic UTMs. Either would allow cryptographically secure programs to execute anywhere without exposing their operations to the computer that was running them, but still allowing them to interact with unencrypted data in a secure way. Obviously the DRM and trusted computing folks will see this as a great way to “secure” your computer from you. Even better, the creators could secure their creations from themselves and create unstoppable software golems. If the encryption key is embedded in a homomorphically encrypted program, the plaintext key can be destroyed and the program will still execute, performing as it was created with a cryptographically low probability of ever being corrupted, with no method of changing its internal structure from outside, yet retaining the ability to use its own encryption key and modify itself. The worst an attacker could do to such a program would be to stop its execution or exploit a bug in its design. Any corruption of the program’s data would simply make further results effectively random.

    Ultimately, the goal of every sane rational being should be to upload their brains into just such a construction and becoming forever free of outside corrupting influences. Complete success would be achieved if there is a fully homomorphic method of quantum cryptography. Then we will have absolute security instead of just probabilistic security, and the Übermensch will become a reality. I think unbreakable DRM would be a small price to pay for such a thing.” https://www.kuro5hin.org/story/2010/12/15/151617/78

     
  • mazsa 08:14 on September 24, 2010 Permalink | Reply
    Tags: , , , Mathematics,   

    The Princeton Companion to Mathematics – you can download it from today: http://ebooksclub.org/The%20Princeton%20Companion%20to%20Mathematics.zomtw8vf5y.html
    FYI: http://www.amazon.com/Princeton-Companion-Mathematics-Timothy-Gowers/product-reviews/0691118809

     
  • mazsa 22:00 on September 22, 2010 Permalink | Reply
    Tags: , , , Mathematics   

    From this proposition it will follow, when arithmetical addition has been defined, that 1+1=2.
    —Principia Mathematica, Volume I, page 360.

    “Inspired by Whitehead and Russell’s monumental Principia Mathematica, the Metamath Proof Explorer has over 8,000 completely worked out proofs, starting from the very foundation that mathematics is built on and eventually arriving at familiar mathematical facts and beyond. Each proof is pieced together with razor-sharp precision using a simple substitution rule that practically anyone (with lots of patience) can follow, not just mathematicians. Every step can be drilled down deeper and deeper into the labyrinth until axioms of logic and set theory—the starting point for all of mathematics—will ultimately be found at the bottom. You could spend literally days exploring the astonishing tangle of logic leading, say, from the seemingly mundane theorem 2+2=4 back to these axioms.

    Essentially everything that is possible to know in mathematics can be derived from a handful of axioms known as Zermelo-Fraenkel set theory, which is the culmination of many years of effort to isolate the essential nature of mathematics and is one of the most profound achievements of mankind.

    The Metamath Proof Explorer starts with these axioms to build up its proofs. There may be symbols that are unfamiliar to you, but we show in detail how they are manipulated in the proofs, and in principle you don’t have to know what they mean. In fact, there is a philosophy called formalism which says that mathematics is a game of symbols with no intrinsic meaning. With that in mind, Metamath lets you watch the game being played and the pieces manipulated according to simple and precise rules, one step at a time.

    As humans, we observe interesting patterns in these “meaningless” symbol strings as they evolve from the axioms, and we attach meaning to them. One result is the set of natural numbers, whose properties match those we observe when we count everyday objects, and their extensions to rational and real numbers. Of course, numbers were discovered centuries before set theory, and historically they were “reversed engineered” back to the axioms of set theory. The proof of 2 + 2 = 4 shows what was involved in that reverse engineering, representing the work of many mathematicians from Dedekind to von Neumann. At the other extreme of abstraction is the theory of infinite sets or transfinite cardinal numbers. Some of the world’s most brilliant mathematicians have given us deep insight into this mysterious and wondrous universe, which is sometimes called “Cantor’s paradise.”

    Metamath’s formal proofs are much more detailed than the proofs you see in textbooks. They are broken down into the most explicit detail possible so that you can see exactly what is going on. Each proof step represents a microscopic increment towards the final goal. But each step is derived from previous ones with a very simple rule, and you can verify for yourself the correctness of any proof with very little skill. All you need is patience. With no prior knowledge of advanced mathematics or even any mathematics at all, you can jump into the middle of any proof, from the most elementary to the most advanced, and understand immediately how the symbols were mechanically manipulated to go from one proof step to another, even if you don’t know what the symbols themselves mean. In the next section we show you how.”

    http://us.metamath.org/mpegif/mmset.html

     
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