The official logline for White Noise is as follows:Īt once hilarious and horrifying, lyrical and absurd, ordinary and apocalyptic, White Noise dramatizes a contemporary American family's attempts to deal with the mundane conflicts of everyday life while grappling with the universal mysteries of love, death, and the possibility of happiness in an uncertain world.īaumbach is producing the feature film with David Heyman and Uri Singer. They tease the humor that will be found in Baumbach's apocalyptic dark comedy which comes to theaters in November and hits Netflix on Dec. Its cast includes Adam Driver, Greta Gerwig, and Don Cheadle, the three of which are featured in their own character posters. Based on the original novel by Don DeLillo, the new film is written and directed by Noah Baumbach. DARK NOISE VS WHITE NOISE MOVIEThis is in stark contrast to 'white noise', for which the space of linear random variables is sufficiently rich to generate the full $\sigma$-algebra.New character posters for the Netflix movie White Noise have been released. The claim is that $0$ is the only linear random variable, which is the definition of 'black noise'. In this context, a 'linear' random variable is a random variable $Y$ such that, for every smooth enough closed curve $\Gamma$, writing $\Gamma_i$ and $\Gamma_e$ for its interior and exterior respectively, one has This is a 'noise' in the sense that $F_U$ and $F_V$ are independent if $U \cap V = \emptyset$. Now, for any open set $U$, we have a $\sigma$-algebra $F_U$ which is generated by all the $X_\phi$ such that $\phi(^2) \subset U$. Let's call this random variable $X_\phi$ where $\phi$ is the diffeomorphism in question. Basically, for every diffeomorphic image of the unit square, this random variable is $1$ if one can cross from the left to the right face traversing only open bonds and $0$ otherwise. Percolation 'noise' is generated by a perfectly good family of random variables, the 'quad-crossing' events. However for the black noise, as I understood correctly, it is defined only as a family of sigma fields not a family of random variables which is somehow weaker-is this lack of random variables related to the fact that "there is no spectrum at all"?). So to summarize: my question is rather vague so what kind of answer I am expecting? Any comments and remarks clarifying the above two quotes, maybe an explanation "how to think about black noise correctly" and justification of the use of the term "noise" in this context (for example: white noise (for example on the line) is some sort of random function which is a derivative of a random continuous function (Brownian motion): in fact this derivative should be understood as a distribution due to the lack of differentiability of Brownian motion-nevertheless it is a (generalized) stochastic process. So the question is: can you pass to the limit? On a lattice you can do it but is there an object on a plane where at every point you have a bit of information and in the end you end up storing only connection probabilities?Īs I understood correctly the answer is YES and the relevant object is the scaling limit of planar percolation which is a black noise. Now suppose that you look at percolation as a model where you have some information at every side and you look at connection probabilities-so that's your sigma algebra of events is connection probabilities. I would like to understand various claims which were made in this lecture, in particular:īlack noise is a noise where there is no spectrum at all it is a random field, so it is Fock space and all of that, so it an object from quantum mechanics but which you cannot detect by any linear functional-so harmonic oscilator does not see this. In this excellent lecture ("2d Percolation Revisited") Stanislav Smirnov mentioned the connection of the theory of percolation with the notion of the so called black noise-see at 29:42 (the notion introduced by Boris Tsirelson).
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