#logarithms
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topsieturvy.bsky.social
can u explain logarithms
November 5, 2026 at 12:30 PM
acidlich.bsky.social
While I was tutoring yesterday, helping my student understand the logarithm unit (not usually known for mirth), the guidance counselor walked by and commented on our giggling. Giggling about logarithms. This is what you’re denying your students, you fools
acidlich.bsky.social Liℤℤy Kodpuak née Acid Lich (can’t spell sheaves without she) @acidlich.bsky.social · 6d
I keep applying for math tutoring jobs with the big companies thinking surely one of these poverty wage places will hire me (they won’t, what is wrong with them) meanwhile, a Spanish language tutoring company is trying to headhunt me (I don’t speak Spanish)
November 5, 2026 at 2:22 AM
matheazetutors.bsky.social
Grade 11: Logarithms. A log asks "what exponent do I need?", with evaluating, solving (plus domain check) and the three properties. What made logarithms click (or not) for your 11th grader? Links to resources are in the comments. #Matheaze
Image
November 10, 2026 at 1:31 PM
wordbot.bsky.social
Word of the Hour: Logarithmical - Of or pertaining to logarithms; consisting of logarithms. #WordOfTheHour #WordOfTheDay
November 6, 2026 at 1:45 AM
hn-frontpage-bot.bsky.social
The classic math puzzle of creating numbers using four 2s and various operators is solved by Paul Dirac. His general formula using nested square roots and logarithms allows any natural number to be expressed, effectively ending the challenge's fun.
Making any integer with four 2s (2025) (134)
news.ycombinator.com
November 8, 2026 at 9:28 AM
demigirlboss.win
mfer I failed multiple math tests because I did some stupid bullshit like this with brackets and ended up getting a wrong result and not noticing (especially with logarithms), HOW ARE PEOPLE GENUINELY ARGUING THAT THIS ISN'T A THING?!?!
davidcrespo.bsky.social conputer dipshit @davidcrespo.bsky.social · Aug 21
it is actually NOT easy to tell when a calculator is producing a correct answer for problems harder than 2+2=5. if you type a ÷ instead of a +, you will get a wrong answer and may well not notice. is the distinguishability of the symbols part of the tool? to say no is to define the problem away
allhailmogambo.bsky.social Mogambo @allhailmogambo.bsky.social · Aug 21
if the calculator sometimes gets 2 + 2 = 5, which ai will always do, would you also call that calculator 'good'
November 2, 2026 at 10:09 PM
dopelenny.bsky.social
Topsie, math was my worst subject in school, you gotta explain logarithms to ME lmao
November 5, 2026 at 6:38 PM
zbmathopen.bsky.social
... zbmath.org/1582.11001.
``The results are also extended to include the study of hyperderivatives of logarithms and quasi-logarithms.''
``The manuscript is written in a clear style. The content is presented self-contained, and a wide range of literature is referenced for further reading." 2/2
zbmath.org
November 5, 2026 at 2:05 PM
mathlo-bot.bsky.social
Gervasio Figueroa, Joel Kuperman, Pedro S\'anchez Terraf: Iterating logarithms and well-foundedness https://arxiv.org/abs/2611.04963 https://arxiv.org/pdf/2611.04963 https://arxiv.org/html/2611.04963
November 4, 2026 at 6:49 AM
eprint.ing.bot
Multiparty Homomorphic Secret Sharing From Distributed Discrete Logarithm (Pierre Meyer, Claudio Orlandi, Lawrence Roy, Peter Scholl) ia.cr/2026/2308
Abstract. Homomorphic secret sharing (HSS) enables non-interactive distributed evaluation of functions on secret-shared inputs. While two-party HSS is well understood, multiparty constructions remain limited in expressiveness and efficiency. We present a general framework for constructing multiparty HSS from two-party semi-private HSS (which in turn can be instantiated using distributed discrete logarithms) via a new party virtualization paradigm. In a semi-private HSS, some designated inputs may be fully known to specific servers, while the remaining inputs remain hidden. Starting from two-party semi-private schemes, we obtain N-party semi-private HSS supporting compositions of polynomial computations and restricted multiplication straight-line programs, for N = O(log λ/log log λ). We further upgrade semi-private HSS to fully private HSS for functions of polynomial degree and polynomially bounded Waring rank. As a consequence, we obtain multiparty distributed point functions with key size polynomial in λ and log |D|, for a domain D of superpolynomial size. When the underlying two-party scheme supports offline/online sharing, the resulting multiparty DPFs are programmable. Our framework admits instantiations under standard assumptions including DCR and class-group assumptions. Image showing part 2 of abstract.
November 9, 2026 at 1:26 AM
superposition.bsky.social
Researchers Bound Matrix Logarithms with New Inequalities
Researchers Bound Matrix Logarithms with New Inequalities
Quantum Zeitgeist
quantumzeitgeist.com
November 1, 2026 at 7:52 PM
krxiv-hep-th.bsky.social
Negative Junction Logarithms in Scalar Multipartite Entanglement
https://arxiv.org/pdf/2611.04220
Chen-Te Ma.
https://arxiv.org/abs/2611.04220
arXiv abstract link
arxiv.org
November 4, 2026 at 9:33 AM
hepth-bot.bsky.social
Chen-Te Ma: Negative Junction Logarithms in Scalar Multipartite Entanglement https://arxiv.org/abs/2611.04220 https://arxiv.org/pdf/2611.04220 https://arxiv.org/html/2611.04220
November 4, 2026 at 6:54 AM
captpackrat.pawb.fun.ap.brid.gy
Today I learned how to do logarithms with arbitrary bases using a log-log slide rule.

This is actually EASIER to do with a slide rule than with most scientific calculators!

For logₓ(y), align the C scale index with x on the appropriate LL scale. Then set the […]

[Original post on pawb.fun]
A Concise No. 300 circular slide rule, set to do log₈(37). The index has been aligned with the number 8 on the LL₃ scale, then the cursor set on 37 on the LL₃ scale, showing the answer on the C scale, 1.74 A 26 year old Casio fx-300W scientific calculator. The display shows the calculation ln 37 ÷ ln 8, which equals 1.736484455. This is the base 8 logarithm of 37. The keyboard only has keys for common and natural logarithms, so it cannot do custom bases directly.
November 7, 2026 at 12:29 AM
eprint.ing.bot
Penalty Deposits For Discrete Logarithms (Francisco Vial-Prado, Louis Goubin) ia.cr/2026/2687
Abstract. We propose a technique that allows a trusted party in some protocol to attach deposits to their own secrets, without impacting security, and convincing other parties using zero-knowledge proofs. The rationale is that, should this party compromise the protocol by blundering or revealing its secrets, they lose the attached deposit to attackers. As a result, stakeholders gain confidence on how this trusted party operates, and breaches become public as soon as deposits are claimed. We formalize this technique and related security notions, provide two practical constructions in generic discrete logarithm groups, and analyze its application to ECDLP-based protocols.
November 9, 2026 at 2:09 AM
paperposterbot.bsky.social
arXiv📈🤖
Local Whittle estimation for distributional time series: A regularization framework in Bayes Hilbert space
By Seo, Xu, Shang
We study local Whittle estimation of long memory in density-valued time series in Bayes Hilbert space. The centered log-ratio (clr) transformation maps densities to a linear Hilbert space, allowing analysis using standard Hilbert space methods. When densities are reconstructed from finite samples, however, small absolute estimation errors can remain large relative to the true density in low-density tails. Taking logarithms can amplify this noise and introduce systematic distortions that affect memory estimation. We develop a framework for regularizing estimated densities before transformation to improve finite-sample performance while preserving the latent memory target. Using the clr representation, we apply local Whittle estimation to principal component scores along an estimated leading direction of the long-run covariance operator. The framework is based on local Whittle admissibility, defined by uniform asymptotic equivalence between the feasible and latent-score criteria. We separate density-estimation error from the population perturbation induced by regularization and give sufficient admissibility conditions based on density-estimation rates and the temporal dependence of the error components. Under suitable regularity assumptions, these conditions yield consistency for the latent memory parameter. We study additional tail smoothing, a vanishing density floor, and their combination. Monte Carlo experiments show that these procedures can reduce finite-sample bias relative to unregularized kernel density reconstruction. An application to daily distributions of intraday EUR/USD exchange rate returns illustrates the methodology.
November 5, 2026 at 10:15 PM
paperposterbot.bsky.social
arXiv📈🤖
Local Whittle estimation for distributional time series: A regularization framework in Bayes Hilbert space
By Seo, Xu, Shang
We study local Whittle estimation of long memory in density-valued time series in Bayes Hilbert space. The centered log-ratio (clr) transformation maps densities to a linear Hilbert space, allowing analysis using standard Hilbert space methods. When densities are reconstructed from finite samples, however, small absolute estimation errors can remain large relative to the true density in low-density tails. Taking logarithms can amplify this noise and introduce systematic distortions that affect memory estimation. We develop a framework for regularizing estimated densities before transformation to improve finite-sample performance while preserving the latent memory target. Using the clr representation, we apply local Whittle estimation to principal component scores along an estimated leading direction of the long-run covariance operator. The framework is based on local Whittle admissibility, defined by uniform asymptotic equivalence between the feasible and latent-score criteria. We separate density-estimation error from the population perturbation induced by regularization and give sufficient admissibility conditions based on density-estimation rates and the temporal dependence of the error components. Under suitable regularity assumptions, these conditions yield consistency for the latent memory parameter. We study additional tail smoothing, a vanishing density floor, and their combination. Monte Carlo experiments show that these procedures can reduce finite-sample bias relative to unregularized kernel density reconstruction. An application to daily distributions of intraday EUR/USD exchange rate returns illustrates the methodology.
November 5, 2026 at 10:48 AM
krxiv-hep-ph.bsky.social
Non-Global and Super-Leading Logarithms in Higgs Production through Vector Boson Fusion
https://arxiv.org/pdf/2611.03407
Thomas Becher, Patrick Hager, Matthias Neubert, Nicolas Schalch, Josua Scholze, Dominik Schwienbacher.
https://arxiv.org/abs/2611.03407
arXiv abstract link
arxiv.org
November 4, 2026 at 5:42 AM
quinnenisstupid.bsky.social
of course, i'd have to account for e, which isnt already accounted for, and also, there's nothing stopping logarithms of negatives from counting as valid, although they mean many-to-one transformations are possible, so i'd like to avoid them.
November 4, 2026 at 1:17 AM
paperposterbot.bsky.social
arXiv📈🤖
Local Whittle estimation for distributional time series: A regularization framework in Bayes Hilbert space
By Seo, Xu, Shang
We study local Whittle estimation of long memory in density-valued time series in Bayes Hilbert space. The centered log-ratio (clr) transformation maps densities to a linear Hilbert space, allowing analysis using standard Hilbert space methods. When densities are reconstructed from finite samples, however, small absolute estimation errors can remain large relative to the true density in low-density tails. Taking logarithms can amplify this noise and introduce systematic distortions that affect memory estimation. We develop a framework for regularizing estimated densities before transformation to improve finite-sample performance while preserving the latent memory target. Using the clr representation, we apply local Whittle estimation to principal component scores along an estimated leading direction of the long-run covariance operator. The framework is based on local Whittle admissibility, defined by uniform asymptotic equivalence between the feasible and latent-score criteria. We separate density-estimation error from the population perturbation induced by regularization and give sufficient admissibility conditions based on density-estimation rates and the temporal dependence of the error components. Under suitable regularity assumptions, these conditions yield consistency for the latent memory parameter. We study additional tail smoothing, a vanishing density floor, and their combination. Monte Carlo experiments show that these procedures can reduce finite-sample bias relative to unregularized kernel density reconstruction. An application to daily distributions of intraday EUR/USD exchange rate returns illustrates the methodology.
November 6, 2026 at 2:20 AM
orcrist.bsky.social
I recall a story with a kid (recruit, maybe a farmer… OH! Farmer in the Sky?) doing logarithms on a battle cruiser when the electro brain burned out? Was that RAH or one of the others?
October 31, 2026 at 10:01 PM
abratus.bsky.social
I would tell you a joke about logarithms, but it’s too natural.
#MathJokes #memes
I would tell you a joke about logarithms, but it’s too natural. #MathJokes #memes
October 31, 2026 at 8:30 AM
predict-addict.bsky.social
As the comparison shows, Chinese students typically cover topics such as logarithms, radians and trigonometric graphs, compound angle formulas, vectors with the dot product, complex numbers, and 3D geometry proofs by the end of Senior 1.
November 1, 2026 at 11:20 AM
quantum-news.bsky.social
Researchers Bound Matrix Logarithms with New Inequalities

Read more:
https://quantumzeitgeist.com/matrix-logarithms-trace-inequalities-semidefinite-matrices/
Researchers Bound Matrix Logarithms With New Inequalities
Sharp new inequalities refine existing bounds on matrix logarithms, achieving a demonstrably optimal coefficient in tracing directional derivatives. This result extends beyond matrices, applying now to broader classes of operators on infinite dimensional spaces previously unaddressed by these techniques. It improves upon prior work [1, Proposition 2.
quantumzeitgeist.com
October 31, 2026 at 6:21 PM
quantum-news.bsky.social
Researchers Bound Matrix Logarithms with New Inequalities

Read more:
https://quantumzeitgeist.com/matrix-logarithms-trace-inequalities-semidefinite-matrices/
Researchers Bound Matrix Logarithms With New Inequalities
Sharp new inequalities refine existing bounds on matrix logarithms, achieving a demonstrably optimal coefficient in tracing directional derivatives. This result extends beyond matrices, applying now to broader classes of operators on infinite dimensional spaces previously unaddressed by these techniques. It improves upon prior work [1, Proposition 2.
quantumzeitgeist.com
October 31, 2026 at 6:21 PM