What made them mysterious? Aren't there always some fraction of atoms or molecules with sufficiently high energy to escape the object?
Can someone help me understand this? I thought that things were supposed to be stable given the elements used for le grand k. That they don't decay on their own and it would have to be another mechanism to explain the divergence?
[0] https://en.wikipedia.org/wiki/International_Prototype_of_the...
But, Le grand K is made of naturally occurring platinum of which most of the isotopes are observationally stable[0] and the one isotope that isn't has a half-life of 6.5×10^11 and only makes up 0.012% [1].
So yeah I don't buy the unstable explanation to even begin to show the divergence, let alone "weight gain".
[0] https://en.wikipedia.org/wiki/Stable_nuclide#Still-unobserve...
[1] https://en.wikipedia.org/wiki/Isotopes_of_platinum
[Edit] Wait are you describing evaporation?
Maybe these aren't the best sources of historic mass data.
And yeah, the mystery is just what mechanism exactly affected each one. (AKA, not much of a mystery.) The possibilities are very well understood.
Ahh, that makes more sense. Thanks!
A test for this theory would have to involve a means of accounting for these kinds of fluctuations.
Wouldn’t just moving an object change its mass? Any change in potential energy would mean a change in mass from good old e=mc^2
You expect simple explanations to VERY complex problems from random internet commenters. I think you expect too much.
* it’s not like there aren’t good theories but you can’t experiment directly on “the” kg because you can’t risk changing it!
Like if you find that your car has broken down after 200k miles, you might not be able to determine the cause, but it wouldn't exactly be some kind of mysterious physical phenomenon that would puzzle scientists. Obviously, something wore out. Why/how is this any different?
A useful paragraph is the following: "The trend during the past century had been for most of BIPM's official copies to gain mass relative to the IPK, although by somewhat different amounts, averaging around 50 micrograms (millionths of a gram) over 100 years. But an alternative explanation is that the IPK was losing mass relative to its copies. Even more likely, it was a combination of both."
Those pages are for the lay audience but you can do your own web search (probably even an algolia search of HN) to know more.
In general, it's often easy to come up with an explanation of some new phenomenon, but to answer the question you still have to do science...which often simply confirms intuition but not always. My comment was less on the reason and more on the difficulty of doing experiments on what was literally the kg, no matter how it fluctuated.
I'm just some random guy on the internet, I know. It's fun to have theories!
Sure, the explanation might not fit in the margins here, but then a link to a source that does attempt to explain it would be fine too.
> The reason for this drift has eluded physicists who have dedicated their careers to the SI unit of mass. No plausible mechanism has been proposed to explain either a steady decrease in the mass of the IPK, or an increase in that of its replicas dispersed throughout the world
https://en.m.wikipedia.org/wiki/International_Prototype_of_t...
OPs question is not ridiculous, nor does he suggest it to counter the "mysterious" claims
1. I am wrong and could learn something new.
2. They are wrong and their opposition fills me with defiant determination.
The difficulty comes when you view something as case 2 but it is actually case 1 and you embarrass yourself. I do this all the time.
The mystery being discussed is that, even after the obvious sources of error are allowed for, there is still a discrepancy, and it's not easy to determine how much of that discrepancy is with the weights being recalibrated vs the test standard they're being calibrated to. None of which is shocking to anyone involved, just puzzling.
I can think of one example in software deployment frequency. The observation (many years ago), was that it's painful and risky (therefore, expensive) to deploy software, so we should do it as infrequently as the market will allow.
Many companies used to be on annual release schedules, some even longer. Many organizations still resist deploying software more than every couple/few weeks.
~15 years ago, I was working alongside the other (obviously ignorant) people who believed that when something is painful, slow and repetitive, it should be automated. We believed that software deployment should happen continuously as a total non-event.
I've had to debate this subject with "experts" over and over and over again, and I've never met a single person who, once migrated, wanted to go back to the nightmare of slow, periodic software deployments.
Computers mostly just continue to work when you don't change anything, so that meant after the first week or so after a release, the chance of getting paged dropped dramatically for 3 months.
The amount of politicking was incredible when it came to which features would be in the next push and which features would slip. The planning meetings, the arguments, the capability slashing, the instability that came from all these political decisions. It was not great and this enormous amount of churn literally disappeared when they moved to daily pushes.
And if by "many years ago" you refer to a period where software deployment was mostly offline and through physical media, then it was indeed painful and risky (and therefore expensive). The experts weren't wrong back then.
* have to be a bit vague here, but while working as a research scientist for the US Department of Defense I regularly witnessed and occasionally took part in scenarios where a radical idea turned "expert advice" on its head, or some applied thing completely contradicted established theoretical models in a novel or interesting way. Consistently, the barrier to such advancements was always "experts" telling you that your thing should not / could not work, blocking your efforts, withholding funding, etc., only to be proven wrong. Far too many experts care more about maintaining the status quo than actually advancing the field, and a concerning number are actually on the payroll of various corporations or private interests to actively prevent such advancements.
* over the last 30 years in the AI field, there have been a few major inflection points, Yann LeCun's convolutional neural networks and his more general idea that ANNs stood to gain something by loosely mimicking the complexity of the human brain, for which he was originally ridiculed and largely ignored by the scientific community until convolution revolutionized computer vision; and the rise of large language models, which came out of a whole branch of AI research that had been disregarded for decades and was definitely not seen as a thing that might ever come close to something like AGI, natural language processing.
* going back further in history there are plenty of examples, like quantum mechanics turning the relativistic model on its head, Galileo, etc etc. The common theme is a bunch of conservative, self-described experts scoffing at something that ends up completely redefining their field and making them ultimately look pretty silly and petty. This happens so frequently in history that I think it should just be assumed at all times in all fields, as this dynamic is one of the few true constants throughout history. No one is an expert, no one has perfect knowledge of everything, and the next big advancement will be something that contradicts conventional wisdom.
Admittedly, I derived these beliefs from some of the Socratic teachings I received very early in life, around 6th grade or so back in the late 90s, but they have continually borne fruit for me. Question everything. When debugging, question your most basic assumptions first., "is it plugged in?" etc, etc
It's sort of at a point these days where if you want to find a fruitful research idea, probably best to just browse through conventional wisdom on your topic and question the most fundamental assumptions until you find something fishy.
I apologize for being a bit snide in my original challenge, I'm fairly sensitive to the "why don't you just" attitude, but I agree with pretty much everything you have to say here.
I have a very similar approach around enumerating and testing assumptions when the going gets tough, and similarly have found that has enabled me to solve a handful of problems previously claimed impossible.
I think the tautological issue with our initial framing is that if you're able to easily identify these problems you probably are a subject matter expert. In many ways it's the outsider art of analytical problem solving - established wisdom should not be sacred.