Skip to main content
13 events
when toggle format what by license comment
Dec 29, 2023 at 9:11 vote accept Akira
Dec 29, 2023 at 9:04 history edited Martin Sleziak
edited tags
Dec 29, 2023 at 8:53 answer added leo monsaingeon timeline score: 2
Dec 28, 2023 at 23:20 answer added pseudocydonia timeline score: 1
Nov 2, 2023 at 16:01 comment added plm @Kostya_I so it seems that we should go the other way around: consider discrete entropy as fundamental and recover differential entropy using some regularized limiting process. I think most of what can be said can be found here: profdoc.um.ac.ir/articles/a/1077376.pdf and math.stackexchange.com/questions/4540066/… , but i have to think about it. PS: Sorry again that i messed things up in the beginning, i only know basics and i did not realize there were bad surprises.
Nov 2, 2023 at 15:26 comment added plm @Kostya_I yes im seeing now your comment, i realized after that i was computing with the formula for discrete entropy, assuming it yielded the same result for a Dirac distribution as the formula for differential entropy. Also, the entropy can indeed be negative in the differential case, but "usually" entropy is nonnegative, so i think some factor should be added to make comparisons easier. I may do a web search, later, to see what the conventions are. PS: Sorry i've been editing my comments now, as i was realizing they did not make sense, because of confusions on my part.
Nov 2, 2023 at 15:24 comment added plm FIrst of all i must correct myself: the Dirac measure has differential entropy $H(\delta)=-\infty$, i was using discrete entropy, which is 0 and is generally nonnegative. To pass from differential entropy to discrete entropy i think we have to add a scaling factor like $-\log s$ when computing on intervals of size $s$. Then also @Kostya_I, i think there's a minus sign missing, to make the entropy positive in the discrete case. It is then always nonnegative with the minus sign (or nonpositive if we omit it as Akira).
Nov 2, 2023 at 15:17 comment added Kostya_I @plm, sorry, I don't follow. If $\rho(x)$ is a probability density, then so is $\rho_a(x)=a^d\rho(ax)$ for any $a>0$. We then have $\mathcal{H}(\rho_a)=\mathcal{H}(\rho)-d\log a$. For large $a$, it tends to $+\infty$, while for small $a$, it tends to $-\infty$.
Nov 2, 2023 at 13:58 comment added Kostya_I @Akira, the entropy in your formula is not necessarily non-negative, e.g., if the density is smaller than 1 everywhere, then the integrand is negative.
Nov 2, 2023 at 12:56 comment added plm Hi Akira, do you see many people call this Boltzmann entropy ? I'd say "differential entropy", "Gibbs entropy", or just "entropy",. I think that Boltzmann was only interested in uniform measures -or rather trivial measures, on a single microstate, as the formula engraved on his tombstone indicates. I don't think this set is compact: take 2 0-entropy (Dirac) measures, $C=0$, make them move apart on $\mathbb R$, their distance tends to infinity. You can do the same with any single probability measure. You may also make up examples with classical distributions whose entropies are known and match.
Nov 2, 2023 at 12:51 comment added Akira @Kostya_I Thank you so much for your help! I follow the convention in optimal transport that the Boltzmann entropy is non-negative. In $\mathcal{P}^2_{ac}(\mathbb{R}^d)$, I identify a measure with its density.
Nov 2, 2023 at 12:47 comment added Kostya_I Clearly not, since you can take $\rho_n(x)=\rho(x-x_n)$ with $x_n\to\infty$, and this has a fixed entropy but no convergent subsequence. Also, is you formula for entropy missing a - sign? And shouldn't you call $\rho$ densities rather than measures?
Nov 2, 2023 at 12:27 history asked Akira CC BY-SA 4.0