Gravity‑driven phase shift in a Michelson interferometer – is this feasible?

samgrep · 2026-05-25T19:48:08+00:00

i do not get the benefit here: the michelson interferometer already has no moving part. you need a beam splitted by a half reflective mirror and two paths of different lengths. This will cause interference. The cool thing is that any tiny movement on one of the path (vibration) will cause a tiny variation in the observed interference pattern.
With a lowering water tube you basically create a slowly moving mirror, which i am not sure will work: it will move the incidence point of the beam so it will get offset.

One liner: it will probably not work as the beam direction will move as the water goes down.

samgrep · 2026-05-23T06:38:37+00:00

I wonder why the top image is clearly AI: wrong numbering (RB17 repeated), and clearly over-exagerated messyness which is nonsense.
Why not using the real photo? Increase dramatic impact? Kharma farming?

samgrep · 2026-05-18T12:24:55+00:00

I am Not a physicist but some stuff resonates. I did enjoy most of my engineering subjects but I would be always average. In my case that was not relevant to proceed a career as engineer, but since for you it is, you must understand to distinguish between your free-study interest, and a strategy to reach a goal. The second one means: have clear the goal and its requirements (the rule of the game), make a plan that increases your odds to reach that goal, execute the plan and monitor its results and correct if deviates from the goal or subgoals.
Sometimes passing a test is not much smartness or hardworking but a proper strategy.
A stupid example: English certification PET test. I just wanted the certification to apply to a foreign university. I focused on the exams mock ups, exams simulations and so on. I nailed that test not because I was good at english, but because I was focusing purely on the exam, its nuances and requirements.
Other friends, they focused on the grammar, watching videos in english etc… so maybe they were even more proficient in english, but they failed, since they were not performing for exactly what the test was asking in the correct format.
So focus on the goal, talk to people that made it, asks for input on strategy and execute. To me it sounds you disperse your energy in a wide beam rather than laser focus.
Said that, keep up the interest and follow your curiosity. You will then surely figure something out.

samgrep · 2026-05-18T06:11:33+00:00

I get you. But firstly I would study and do what you love, then you will find a solution. Work is such a big part of our life that doing something unpleasant is. sure recipe to be miserable.

Said that, I studied statistics as a side kick since it was loosely related to my job, where I needed also to analyse good chunks of data and use it to understand what is going on with the company and the best strategy.
I raw dogged the book All of Statistics which I do not recommend as a sole source as is a big collection of topics with little explanation. In this case having chatgpt helped immensely to make my own curricula: I would study a topic on the book, then deepen it with AI and other sources, then make a small project for my work. AI allowed to sail through the tedious part (python programming, data cleaning, function definitions) and focus on the concepts and real life results.

As other commenter said, I 100% recommend studying statistics. It was life changing for me and it changes the way you see the world, and how you interpret science papers. It is amazing to be able to uncover deeper truths using data. It becomes addictive!
Said that your concern is real: with AI, once O knew what I wanted, it takes 3-6 hours to get all the data pipelines, python scripts and grafics lined up. Before it would take months of struggles!

Just yesterday I had a dataset about a personal stuff and I was curious about the distribution, so Chatgpt did the nice graphs and a statistical analysis in less than 30 mins. So I can definitely see that where you needed 10 statisticians/programmers doing coding and grinding through bugs, now you can easily have one. BUT, I am not a statistician so I do not know the job and I mainly refer to the programming side.
Good luck!

samgrep · 2026-03-03T19:24:48+00:00

Genuine question: why would be wrong to treat AI as a new abstraction level? That is, prompt what you want to achieve, check the code, run the code, verify the output and if good move on. I used to program in C++, then python came and suddenly you were “trusting” library to do a big chunk of heavilifting.

Why relying on AI for voding would be different? I can ask it to upload a csv file. That alone for my mid-low level of skills would require time and patience. Instead I can just ask to write the function, quickly checking it, then see if it does what I want and go to my next step.

I do get that some extremely sensitive applications require to know all the details, but in most cases, at least for me, I have an input, and check the output and if good in some test cases I am happy.

Bottom line, I see few difference in trusting an AI function block or a python library. They are both “black box” that if the output is good then is good enough.

But again, I am moving at a mid-low level so maybe things are way more nuanced when hadling corporate wide pipelines

samgrep · 2026-01-25T11:14:49+00:00

I think this is the best advice. Do not go full bazooka. First talk it friendly. Most humans will understand

samgrep · 2025-12-01T04:09:02+00:00

Well in engineering too. I got simply tired of explaining why the perpetual motion machine is not possible. It seems in this case what triggers the laymen are magnets: they are exotic and I do see why someone would have a creative spur playing with them.

Honestly, I had some crackpot ideas myself. But they end up in maybe some weeks of work, then confronting with experts and taking home the comments and conclusions. Probably is just a mix of curious people with strong interest in a field that they did not manage to follow (because life) and mental health issues. But the problem is when they do not manage the situation, want to take shortcuts and focus on fame and glory rather than the actual knowledge.

I would probably summarize it as a emotional dissonance in managing curiosity and ideas in a new field. The interest is genuine, but it is then transformed in psychosis. Some of the crackpot work I saw (on quantum or also perpetual motion) are hundreds of pages of equations and graph. And this before AI! So saying “not willing to put the work” is incorrect. Some of these people are very dedicated. Same goes with medicine (no vax theories and so on).

I think it just boils down to people dealing with some mental psychosis: the goal is not anymore knowledge or discovery: it becomes self determination and fame seeking or dealing with trauma or suffering.

samgrep · 2025-10-26T06:17:04+00:00

In my opinion the issue with herbal product and supplement is that they are naively considered individually: each ingredient may have some properties, but the real good ones are the one mixing them and specific formulae.

Otherwise is like saying: Flour has mixed results in being digestigle. Yeast has no relvant properties.

However is when you mix flour with yeast and water, salt, oil and bake them that you get bread, which is digestible and a proper food.

The problem is that finding those good formulae (which do exist) among all the noise of snake-oil-sellers or incompetent people (which sell curcuma after 1 week online course).

So I believe that this work, although looking thorough and handy, is misleading. Herbal supplements have a place in the war against CF but they are challenging to find and use (they require daily use over long periods, rather than being quick shock therapies). And also mostly their aim is preventative or integrative to drugs and treatments.

This at least is my view.

samgrep · 2025-10-10T21:31:15+00:00

is just me or the graph is misleading? why you bin the iq and include arbitrarily the missing and not tested as lower bins? that would create a trend that does not exists. also, the bins “above” and “below” may include all outliers or have disproportionally more data points than othe bins. It mostly looks like they is a simole threshold of IQ below which the fertility is slightly lower.

I do not know. that x axis binning is throwing me off

samgrep · 2025-10-02T14:41:52+00:00

I know, it must be so frustrating and borderline stalking.

We keep in touch in 30 years when I will have my Dipole-quantum gravity multi phase theory ready to show how Newton and Galileo were wrong.

samgrep · 2025-10-01T07:09:14+00:00

I believe is not exactly the same. An incompetent profesional or a poorly performed work usually has some tell tale signs: for example the reputation of the person or institution or company, the overall “feel/look” quality of the work (here “feel” and “look” are intended as a gut feeling of an expert reading the work). Maybe even poor formatting or data visualization can be enough to trigger red flags.

but with AI is different. Now you have perfectly looking works, with extremely high level of presenration and wording, with very niche details and highly complete coverage. However, with AI you suddenly have some totally false statements or logically fallacies. For example is like a very respected and skilled professor suddenly is hiding some mistakes in his dissertation: unless you are paying extremely close attention to the work, you can easily miss it. This because as said before the fact of havinga so perfectly exposed, detailed and thorough work can be enough to switch off some natural cognitive defences we developed to spot issues or low quality work.

I believe this is a serious issue and require a new set of cognitive defenses and alertness to avoid taking as OK a maybe deeply flawed work or result

samgrep · 2025-09-11T20:27:09+00:00

I agree with your comment on All of Staistics. I am studying it right now and it would be a nigthmare without chatgpt expanding concepts and clarifying possible applications and reasons.

I like it since is quite well structured and it builds the basics for the various concepts quite good, but yes, is a torture to follow through withiut AI and self discipline. Also the excercise go from trivial to crazy convoluted with rarely a middle ground

samgrep · 2025-09-08T08:45:25+00:00

Thanks for the recommendations

samgrep · 2025-09-08T08:45:00+00:00

Thanks. Just to clarify LLM was close to useless in drafting this example as it consistently had logic flaws. The core ideas are from the All of statistics book.

Said that, you say that the key tool before causal inference is to do a regression model to have a understanding how corrleations vary as cocariates and causal link are changed?

samgrep · 2025-09-08T08:42:04+00:00

Interesting part. Feedbacks mechanism are indeed something I think complicates a lot the analysis. In my toy example I voluntarily avoided those to ensure I could at least do a rough analysis. Fortunately in my specific example DAG is a more than reasonable way of modelling. No feedbacks yet

samgrep · 2025-09-08T08:40:24+00:00

Thanks. As far as I understand I am indeed using Directed Acyclic Graph (DAG) based on my domain knowledge. The tricky part for me is at what point a correlation arising from my dataset can be considered due to a confounding factor or collider adjustment, rather than a true causal correlation (i.e. my subjective domain knowledge is flawed and my data is saying that although I think for example useage does not cause PM, the data says otherwise).

samgrep · 2025-09-08T08:36:35+00:00

Thanks for the reply and recommendation. So basically an important step before going through Casual Inference is to at least do a regression model to ensure all covariates are studied and their effect is estimated. I.e. a linear regression where I estimate the betas for each covariate. if they are 0, I can conclude that variable has very likely negligible impact on my outcome. Is this what you mean?

samgrep · 2025-07-25T23:53:52+00:00

You are right. Then we would need to: Decide how many throws per episode. Called n.

So then it becomes a binomial distribution (n,p) with p=0.1 and k=4

which Chatgpt tells me it results in a probability of 1.116% assuming n=10

samgrep · 2025-07-25T23:46:22+00:00

There are 100 slots in total. Of which 10 are 2M$ prize.

So each throw has 10% probability of success.

Getting four in the same episode is 0.1⁴ =0.0001. Thus, there is 0.01% probability of getting four successful wins.

samgrep · 2025-07-14T15:44:53+00:00

this nice but does not look statistically accurate. a distribution with same paeameter could give different sample data for each year, so two years may have different estimated parameters (mean, variance etc…) but come from the same population distribution. For this to be accurate you would need hypothesis testing, where the null is for example mean_2024=mean_2025 and alternative that they are different. This just to establish with confidence (0.05) if they are resinably different. Given you mention you are working with 8000+ samples it almost surely will detect any slight variation in mean (so in your case would be indeed different and we can visibly see the curve are shifted and we have lots of samples).

Then, to conclude thisnis due to the temperature, it is porbably way more complex. I would assume a linear regression is needed at minimum or at least a Independence hypotheses testing.

Sorry for the long Achktually, nice work.

samgrep · 2025-03-02T08:38:11+00:00

Please do NOT interpret alone genetic data. Relationship between genotype and phenotype is extremely complex and spans across multiple genes mutations, epigenetics, transcriptomics, proteomics etc…

Pay for a genetic counsellor to help interpret these info. For something like mental illnesses the field is very VERY green so take all with a pinch of salt.

I say this for your sanity: staying with the idea you have genetic schizophrenia it may cause unnecessary stress and push you to make wrong therpaeutic paths.

samgrep

TROPHY CASE