Author Archives: vznvzn


hi all. what if research into the interpretation of QM leads to a QM + GR path/ direction for unification? that is exactly the ambitious, overarching, but not inconceivable promise of the fluid paradigm of physics.

its been ~¾ a year since a last bold/ ambitious blog on copenhagen interpretation and new fluid ideas in quantum mechanics and physics.

at this point have blogged about ½ decade on some of these subjs and my neurons are really buzzing, crackling and snapping lately at full volume, the field is going thru an identifiable paradigm shift predicted years ago in this blog.

have collected a copious collection of new info/ leads, my links really runneth over. it really looks like nearly critical mass in some ways.

have been waiting to blog on this a few months and looking for an opportune moment. am expecting some massive signs to show up. many have already shown up. am finally deciding to write all this up at the near ½ year point.

one of the biggest signposts/ BREAKTHRUS is the new Becker book, What is Real, the Unfinished Quest for the Meaning of Quantum Physics.[a] havent bought it yet but its on the top of my to-read pile. this is causing big, maybe even massive waves in the mass/ popular media eg NYT but also the scientific journals such as Nature. its being reviewed by top experts positively. major response on social media such as reddit also. maybe a gamechanger.

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collatz new highs

am still clawing/ scrounging for any “big picture” leverage, resuscitating old leads. after some extended musing of new findings, came up with this latest idea. there are lsb triangles even in the disordered climbs for the uncompressed mapping. do these mean anything? seemed to see some cases/ trend where the triangle sizes successively decrease in the climb, ie dont successively increase. can this be quantified? this is somewhat similar to the old workhorse “nonmonotone run length”. instead, its something like “count of new highs” (in bit run lengths either 0/1). that statistic is (maybe not uncoincidentally) used in stock market analysis, which has to deal with some of the most wild/ intractable fractals of all.

it was not hard to wire up the last “dual/ cross-optimizer” (ie both within fixed bit sizes and also increasing bit sizes) to calculate this metric, named here ‘mc’, serving its intended purpose of trying out new ideas quickly. ran it for 100 bit width seeds and then it did indeed seem to flatline somewhat. upped the seed size to 200 bits and then more of a (very gradual) trend is apparent. it looks like a logarithmic increase (‘mc’ red right side scale, other metrics left side scale). ‘mw’ is the # of iterations since last max/ peak run length. the optimizer ran for a long ~650K iterations.

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collatz killer

hi all here we go with the latest installment. trying to come up with new names/ themes. again theres a “pivot” going on at the moment but maybe there are now too many too count. time now for an intermediate retrospective/ pov. my recent physics blog talked about “killing the copenhagen interpretation” and thats my latest idea for this problem. the problem is definitely “killer” in many senses of the word. it kills all great ideas launched against it, its like an impenetrable fortress.

there was a tone of optimism in a lot of prior writing. now looking all that over, it was based on a longtime theme that was yielding fruit(s) of labor(s). the basic idea is that there are locally computable “features” that can, with enough ingenuity, predict longterm glide behavior with high accuracy, and also generally explain other basic trajectory dynamics properties. this clearly ties in with the machine learning approaches. this research theme has been pursued for several years now.

however, last month there was a massive setback on this particular theme/ direction. did you catch it? to summarize, the features being used, mostly based on (binary) density, were leading to a lot of insights and leverage on the problem. but there was a moment a few years ago when the research started to focus on generating density-based seed trajectories instead of more generally. that turned out to be a major detour bordering on a mistake (in 2020 hindsight). 😮 😳 😥 😡 👿 o_O

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cybersec 2018 intl russia infestation/ cyberwar

hi all. what a crazy topic at full possible worldwide volume and really exhausting to track. have been taking a break from misc blogging but sometimes it seems the world is in flames. it took a year to figure out some of the basics of the russian infestation[a] which shows how difficult investigative work can be esp wrt espionage but every day leads to more revelations/ alarm. its clearly an intl full fledged cyberwar at this point larger than any in history. the ejection of russians out of multiple democracies is met with threats of retaliation by russia. there is always the risk, discussed abstractly by military experts, that cyberwar turns into real war. that seems “less unlikely” every day.

  • at this point the outlines of the russian troll factory with a few million dollars a month budget is mostly revealed, a psyop that probably also involved Brexit.[a2]
  • Mueller investigation issued indictments for russian espionage/ psyop operations.
  • looks pretty solid now that russia hacked DNC via Guccifer but also has covered it up. close connections with Guccifer via Roger Stone lead to “high exposure.”
  • to me the murder of seth rich is highly suspect. it made headlines for several months last year but is not any more on the media radar. the family vehemently rejects any “conspiracy theories”.
  • the recent exotic poisoning attempt on a russian double agent in britain and his daughter has raised intl alarm over russian espionage activities. in the publics compartmentalized mind maybe that event has nothing to do with other russian (psy)ops, but anyone in the “biz” knows its all interconnected aka intersectionality.
  • facebook/ zuckerberg are currently caught in a buzzsaw of harsh public opinion related to the cambridge analytica data leak and realization of how deep the russian psyops were without prior detection, a public relations crisis and costing tens of billions in stock price drop.[b] historically facebook goes thru periodic “privacy crises/ scandals” but this looks like the largest ever in its history. looks like that whole decade-long business model of doing journalism for cheap has what might be called hidden costs/ unintended consequences. zuckerberg now admits mistake(s) and being unduly “dismissive” in full page newspaper apologies. 😮 o_O
  • there is serious question about how democracy can persist amidst these serious threats (misinformation, disinforation, propaganda, etc).[d]
  • net neutrality is grabbing lots of headlines lately also.[f]
  • other hostile foreign actors NKorea & China still grab headlines. note there is some affiliation between Russia/ Nkorea/ China.[k]
  • social media[e] is a whitehot topic and theres strong congressional scrutiny at this point.

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collatz trap(s)

the last installment ended with some idea of possible “traps” in certain metrics. this idea occurred to me quite awhile ago and didnt work out under some examination previously but theres some new ways of looking at this. in the past, it is clear that eg there is no strict density trap in the sense of one iterates density bounding the next ones eg wrt to the density core. but the last experiments led to a different idea. what if a metric is bounded over some count of iterations, does that limit future glide potential? its a simple variation, seems to be quite related, but is maybe the key twist that looks more plausible as a measurable/ consistent property.

this new experiment simplifies the code a lot and bounds distance-from-core labelled ‘dc’ and a entropy metric. the entropy is counting total # of 0-to-1 and 1-to-0 transitions in the binary form, scaled by the bit width. the (scaled) inverse entropy formula (aka “order”) ends up as one minus sum of count of 0/ 1 runs/ groups divided by iterate bit width, labelled ‘e’. this upper bound on the inverse entropy is equivalent to a lower bound on the entropy (because as mentioned entropy increases as glides progresses, and the potential trap is at the end; also note a “low upper bound (on order)” is a “high lower bound (on entropy)”). it finds a sharp transition point ‘e’ ≈ 0.40. (as mentioned, suspect that both low and high entropy may be tending to bound glide length, therefore maybe glide bounding wrt density-distance-from-core is inversely related to entropy-distance-from-core?)

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