Build a working game of Tetris in Conway's Game of Life

Question: Here is a theoretical question - one that doesn't afford an easy answer in any case, not even the trivial one.
In Conway's Game of Life, there exist constructs such as the metapixel which allow the Game of Life to simulate any other Game-of-Life rule system as well. In addition, it is known that the Game of Life is Turing-complete.
Your task is to build a cellular automaton using the rules of Conway's game of life that will allow for the playing of a game of Tetris.
Your program will receive input by manually changing the state of the automaton at a specific generation to represent an interrupt (e.g. moving a piece left or right, dropping it, rotating it, or randomly generating a new piece to place onto the grid), counting a specific number of generations as waiting time, and displaying the result somewhere on the automaton. The displayed result must visibly resemble an actual Tetris grid.
Your program will be scored on the following things, in order (with lower criteria acting as tiebreakers for higher criteria):

Bounding box size — the rectangular box with the smallest area that completely contains the given solution wins.
Smaller changes to input — the fewest cells (for the worst case in your automaton) that need to be manually adjusted for an interrupt wins.
Fastest execution — the fewest generations to advance one tick in the simulation wins.
Initial live cell count — smaller count wins.
First to post — earlier post wins.
Comment: Does "demonstrably working example" mean something that runs in a matter of hours, or something that can be proven correct even though it would take until the heat death of the universe to play?
Comment: I am trying to solve this... Now, when I go to bed, I see gliders everywhere, colliding in a giant mess. My sleeps are full of nightmares where pulsating pentadecathlons block my way and Herschels are evolving to absorb me. Please, John Conway, pray for me...
Comment: **This challenge is being worked on!** [Chat room](http://chat.stackexchange.com/rooms/35837/the-quest-for-tetris) | [Progress](http://meta.codegolf.stackexchange.com/questions/2140/sandbox-for-proposed-challenges/8016#8016) | [Blog](http://blog.phinotpi.com/2016/05/30/the-quest-for-tetris/)
Comment: As of 5:10 this morning (9:10 UTC), this question is the first question in PPCG history to reach 100 votes without getting an answer! Well done everyone.
Comment: I'm pretty sure something like this is possible and playable.  It's just that very few people have the expertise to be able to program what is probably one of the more esoteric "assembly languages" in the world.
Comment: Finally there's an answer, after four years.
Comment: Any valid answer to this will probably become the most upvoted answer on this site.
Comment: A [Bitmap Display](http://copy.sh/life/?pattern=pulsarpixeldisplay8x2&step=1024) has been created before. Anybody who gives this a attempt might want to use it.
Comment: @copy Oh my... I wish I could understand this.
Comment: Do you actually have to be able to *see* the block rotating and falling etc., on the game of life grid, or is it enough just to have it logically represented somehow? If the latter then this task isn't impossibly hard - you can just take one of the existing Turing machine implementations, write a compiler for it (if that hasn't been done already), then code up Tetris in the language of your choice. But if the former then, well, I guess it's possible, but it would be a *huge* task for anyone to attempt.
Comment: @wizzwizz4 It probably will, actually.
Comment: "Whats your favorite programing language?"
"Conways game of life"
Comment: I'd already be impressed if anyone can show me a single tetris block which rotates cw and ccw within a defined number of steps. (not the simple four tiles block ;-))
Comment: @JanDvorak and PeterTaylor While it'll probably take a few thousand generations for the solution to complete a single iteration, it should be fairly easy to make it go by quickly. [Golly](http://golly.sourceforge.net) and most other modern cellular automaton simulators have some form of speed control; in addition, since the solution will likely be repetitive, it'll cooperate nicely with Golly's [Hashlife](https://en.wikipedia.org/wiki/Hashlife) algorithm (ensuring that it'll run smoothly at any reasonably fast speed). Point being that we'll be able to see for ourselves that it works.
Comment: @M.I.Wright If you do end up going all-in for a solution, good luck to you. We all want to see you succeed.
Comment: @PeterTaylor and JanDvorak Even a proof would be extremely complex. It is difficult to *proove* that any tetris program in any (much more suitable than GoL) high level programming language works as intended - even more if you have to construct something out of more elementary building blocks.
Comment: @Howard, I think a proof would have to be on the basis of "Here's a program you can examine; here's a compiler which I can prove correct".
Comment: You can submit as many as you want; this question has gone unanswered for two years since I asked it.
Comment: @Pharap As mentioned in the question statement, input is represented by manually changing the state of the automaton at a certain generation.
Comment: has anyone seen my jaw? ...  I dropped it somewhere on this page (near the very top!). This question and the answer is awe inspiring, and I'm glad it exists. Congrats to all involved
Comment: @PeterTaylor: The latter would be fine.
Comment: @Nathaniel Preferably it would be a visible demonstration, since that's what the metapixels are for.
Comment: I'll keep this one up, but I could definitely post a simpler one.
Comment: Jeff Atwood recently retweeted a link to this question: https://twitter.com/balpha/status/908320205591511041
Comment: @PeterTaylor I'd say, given the solution would probably be slower than the decay of electrons, I'd say a mathematical-grade proof is required.
Comment: @M.I Wright: using a central processor is fine, but preferably the result would be visible on the screen.
Comment: Of course! For a display I was thinking of giving data to [this thing](http://conwaylife.com/forums/viewtopic.php?p=4902#p4902), which I think @copy posted up above if you want to see it in action... I've already started on a metapixel, though [is it fine if I submit two? :P]
Comment: @ghosts_in_the_code nope, just hit an unexpected roadblock; the metapixel was *technically* finished, but it didn't work at all since the whole idea of a metapixel is that it works independently. Tetris pieces, however, take up more than one pixel, so they need to be synchronized. I'm still working out the kinks in a new idea - I can actually post a diagram+some info on how it'd work if you're interested.
Comment: @JoeZ. this challenge might be too hard. Perhaps consider reposting something much much simpler? A tic tac toe game in life might be plausible for multiple people here to accomplish in different ways.
Comment: The question says "randomly" generate a piece. Where does one get a source of randomness in CGOL? There's no way to get the current generation or date/time as a seed for a PRNG or anything...
Comment: @mbomb007 - take the same approach as many older games do. You have a PRNG with a static seed, and user input is fed to it. This will have the downside that the first piece is always the same. Alternatively, have your user input setup also take a PRNG seed.
Comment: @mbomb007 It's way too old for any amount of votes to get it onto the HNQ.
Comment: @AudenYoung [**Blog Archive**](https://web.archive.org/web/20190923192327/http://blog.phinotpi.com/2016/05/30/the-quest-for-tetris/)
Comment: Only a few thousand? Sounds more like it would take a few million.
Comment: The OTCA metapixel has a period of 35328; the tetris unit cell will be significantly less complicated than it (can't go into as much detail as I'd like to in 600 chars), so taking into consideration that Hashlife likes powers of two, I'd aim for around 2^14 gens. Also note that using a metapixel as opposed to a central processor of some sort will make features like rotation virtually impossible. [disclaimer: I may or may not be trying my hand at a solution]
Comment: oh, but if the OTCA metapixel's p184 clock is used, it may be easier to keep the same timing. Not sure yet.
Comment: @M.I.Wright I'm not personally interested (neither am I capable) but I would recommend posting your progress anyway, because 1. People can help you find flaws in it. 2. Someone else may be able to solve it by building on your method.
Comment: @M.I.Wright the OCTA metapixel's state change only depends on its eight neighbors. a tetris cell's state change depends on its whole row, among other things. even ignoring control input (assume we just need to simulate a step of a tetris field), the tetris metapixel is going to be much more complex than a game-of-life metapixel
Comment: @Sparr exactly! That's why I ditched the metapixel and am working on my new idea (which i'll get around to summarizing here sooner or later). I also kinda think that a tic tac toe game would be on about the same level of difficulty as this challenge.
Comment: @M.I.Wright tic tac toe should be roughly similar to the life metapixel. the result of a TTT game depends on just 9 cells.
Comment: Just realised that this doesn't have a winning criterion other than "first to post". Once the first solution is posted, it may lower the barrier to entry and result in more solutions. Maybe it would be worth adding a winning criterion before the first solution comes in. Like starting position that fits in the smallest rectangular area, or fastest run speed in terms of arena ticks. That would allow for a basic first solution using existing components for pixels and logic gates, but still leave the competition open for more innovative customised solutions later.
Comment: @trichoplax Maybe something like "fewest initial cells filled in"?
Comment: I wonder if this question can get to 100 upvotes without being answered.
Comment: @JoeZ. that sounds good
Comment: If it affects your decision on whether to edit in a winning criterion, there's some [discussion on meta](http://meta.codegolf.stackexchange.com/q/9288/20283) about this specific challenge.
Comment: Erm... How exactly does one provide input to said game? The standard Conway's Game Of Life provides no input other than the start state.
Comment: @JoeZ. It probably won't reach 150 (un)fortunately!
Comment: @SeeOneRhino Would the code written take any input? Otherwise it wouldn't really be a code challenge.
Comment: @wizzwizz4 No, that was a joke.
Comment: Can you define "Tetris" a bit more? Otherwise I could submit one cell and win, because it *is* tetris, just too small to play.
Comment: @SeeOneRhino I'd _assume_ "Tetris" to mean that you construct a metapixel-like thing that can be tiled to make as large of a board as necessary, but you'd need confirmation from OP.
Comment: I'm surprised this hasn't made the HNQ (Hot Network Questions) list yet.
Comment: @TLW Taking the seed as input is probably the best way to ensure every game can be different.
Comment: exact definition of display?
Comment: @mbomb007 is there any archive of the blog? The link is dead.
Comment: Now you can make [Tetris in Tetris](https://meatfighter.com/tetromino-computer/) in CGOL.
Answer: This began as a quest but ended as an odyssey.
Quest for Tetris Processor, 2,940,928 x 10,295,296
The pattern file, in all its glory, can be found here, viewable in-browser here.
This project is the culmination of the efforts of many users over the course of the past 1 & 1/2 years.  Although the composition of the team has varied over time, the participants as of writing are the following:

PhiNotPi
El'endia Starman
K Zhang
Blue (Muddyfish)
Cows quack (Kritixi Lithos)
Mego
Quartata

We would also like to extend our thanks to 7H3_H4CK3R, Conor O'Brien, and the many other users who have put effort into solving this challenge.
Due to the unprecedented scope of this collaboration, this answer is split in parts across multiple answers written by the members of this team.  Each member will write about specific sub-topics, roughly corresponding to the areas of the project in which they were most involved.
Please distribute any upvotes or bounties across all members of the team.
Table of Contents

Overview
Metapixels and VarLife
Hardware
QFTASM and Cogol
Assembly, Translation, and the Future
New Language and Compiler

Also consider checking out our GitHub organization where we've put all of the code we've written as part of our solution.  Questions can be directed to our development chatroom.

Part 1: Overview
The underlying idea of this project is abstraction.  Rather than develop a Tetris game in Life directly, we slowly ratcheted up the abstraction in a series of steps.  At each layer, we get further away from the difficulties of Life and closer to the construction of a computer that is as easy to program as any other.
First, we used OTCA metapixels as the foundation of our computer. These metapixels are capable of emulating any "life-like" rule.  Wireworld and the Wireworld computer served as important sources of inspiration for this project, so we sought to create a similar constuction with metapixels.  Although it is not possible to emulate Wireworld with OTCA metapixels, it is possible to assign different metapixels different rules and to build metapixel arrangements that function similarly to wires.
The next step was to construct a variety of fundamental logic gates to serve as the basis for the computer.  Already at this stage we are dealing with concepts similar to real-world processor design.  Here is an example of an OR gate, each cell in this image is actually an entire OTCA metapixel.  You can see "electrons" (each representing a single bit of data) enter and leave the gate.  You can also see all of the different metapixel types that we used in our computer: B/S as the black background, B1/S in blue, B2/S in green, and B12/S1 in red.

From here we developed an architecture for our processor.  We spent significant effort on designing an architecture that was both as non-esoteric and as easily-implementable as possible.  Whereas the Wireworld computer used a rudimentary transport-triggered architecture, this project uses a much more flexible RISC architecture complete with multiple opcodes and addressing modes.  We created an assembly language, known as QFTASM (Quest for Tetris Assembly), which guided the construction of our processor.
Our computer is also asynchronous, meaning that there is no global clock controlling the computer.  Rather, the data is accompanied by a clock signal as it flows around the computer, which means we only need to focus on local but not global timings of the computer.
Here is an illustration of our processor architecture:

From here it is just a matter of implementing Tetris on the computer.  To help accomplish this, we have worked on multiple methods of compiling higher-level language to QFTASM.  We have a basic language called Cogol, a second, more advanced language under development, and finally we have an under-construction GCC backend.  The current Tetris program was written in / compiled from Cogol.
Once the final Tetris QFTASM code was generated, the final steps were to assemble from this code to corresponding ROM, and then from metapixels to the underlying Game of Life, completing our construction.
Running Tetris
For those who wish to play Tetris without messing around with the computer, you can run the Tetris source code on the QFTASM interpreter.  Set the RAM display addresses to 3-32 to view the entire game. Here is a permalink for convenience: Tetris in QFTASM.
Game features:

All 7 tetrominoes
Movement, rotation, soft drops
Line clears and scoring
Preview piece
Player inputs inject randomness

Display
Our computer represents the Tetris board as a grid within its memory.  Addresses 10-31 display the board, addresses 5-8 display the preview piece, and address 3 contains the score.
Input
Input to the game is performed by manually editing the contents of RAM address 1.  Using the QFTASM interpreter, this means performing direct writes to address 1.  Look for "Direct write to RAM" on the interpreter's page.  Each move only requires editing a single bit of RAM, and this input register is automatically cleared after the input event has been read.
value     motion
   1      counterclockwise rotation
   2      left
   4      down (soft drop)
   8      right
  16      clockwise rotation

Scoring system
You get a bonus for clearing multiple lines in a single turn.
1 row    =  1 point
2 rows   =  2 points
3 rows   =  4 points
4 rows   =  8 points

Comment: First of all +1, because this is an insanely awesome achievement (especially since you built a computer in game of life, rather than just tetris). Secondly, how fast is the computer and how fast is the tetris game? Is it even remotely playable? (again: this is awesome)
Comment: This is the single greatest thing I've ever scrolled through while understanding very little.
Comment: A warning for anyone wanting to distribute small bounties over the answers: you have to double your bounty amount each time (until you hit 500), so a single person can't give the same amount to every answer unless that amount is 500 rep.
Comment: This... this is completely insane. +1 to all answers right away.
Comment: @Christopher2EZ4RTZ This overview post details the work done by many of the project members (including the actual writing of the overview post). As such, it's appropriate for it to be CW. We were also trying to avoid one person having two posts, because that would cause them to receive an unfair amount of rep, since we're trying to keep the rep even.
Comment: 2,940,928 x 10,407,936? That doesn't sound codegolf like. I was expecting `FS¿⁼ι/↓¶/↘ι` or some equally readable insanity :P
Comment: I've never used the term "mindblowing" before but there's a first time for everything.... Can't even decide which part to single out as most impressive. The thought process, documentation, architecture, implementation, tools, everything is just amazing. Was a *really* interesting read. A big thank you for documenting all of this so well and a standing ovation for your efforts!
Comment: @SocraticPhoenix The computer and Tetris game are fast enough to be played using the JS implementation of VarLife on El'endia's website. At best, the pure-GoL implementation is 35328 times slower, thanks to the period of the OTCA metapixel. In practice, there's a bit of a speedup thanks to HashLife, but also a slowdown because of the absolutely massive GoL pattern being simulated. It's still playable, but slower and more difficult (since there's no nice RAM viewer/editor in Golly like on El'endia's website).
Comment: You guys built a processor in Game of Life... Wow. Holy ****.
Comment: YOU DID IT...I don't know what to say...+1
Comment: Oh shoot, since people are taking note of the fact that you've really managed to create a full-fledged computer, I think it's also worth mentioning that this actually is not the first such computer GoL has seen. That title would rightfully go to Adam P. Goucher's 2009 metacell-less [universal computer+constructor](http://pentadecathlon.com/lifeNews/2009/08/post.html) -- although your 'QFTUC' is by a long shot the first to actually support a viable program :P (not to mention a real human-readable compiled language, amazing!!)
Comment: Something I love about this project and its explanations: it's essentially a free course on computer architecture. I understand more about processors and assembly language and compilers now than I did before reading these posts.
Comment: So now to solve other PPCG puzzles using QFTASM or the higher-level languages?
Comment: [Obligatory XKCD](https://xkcd.com/505/). Congratulations on taking less time than "eternity" to solve this one. :^D
Comment: While I have to congratulate the effort, I have to say this methodology is sort of like deciding to reinvent the wheel by gluing a bunch of tiny little modded wheels together lol. Suppose I don't have much room to talk here since I never finished the version I wanted to submit, though. Good work :)
Comment: Is there a way to graphically view the Life simulation itself? I realize it would need to execute so fast it would basically be a blur, but I'd still love to be able to watch in spite of that. It isn't quite the same that I *know* that this is GoL, but can't actually *see* it. (If this is in fact possible and I'm just not seeing how, my apologies; what am I missing?)
Comment: Jesus christ you designed a entire programming language and CPU in conway's game of life. I ... what even is this :o
Comment: Can this kind of thing be submitted for a doctoral thesis lol?
Comment: @qw3n: I know it's meant as a joke. But yes, certainly.
Comment: It's too bad there's no nice interface to the full GoL version. Maybe someone can figure out how to easily visualize the memory in Golly, and maybe figure out how to set RAM values.
Comment: @i336_ Part 5 has a file you can load into Golly to watch it.
Comment: 3 years later, still absolutely insan
Comment: Wow.. just.. wow.. WELL DONE
Comment: Also, the current version (http://play.starmaninnovations.com/qftasm/#jllHdnBGSP) has a bug - if you move your piece left/right until it collides with the wall, it sticks there (!) as if it had been dropped (but hanging in midair): https://i.stack.imgur.com/vYTsL.png. Since it's QFTASM though I guess this should be easy to fix!
Comment: @nneonneo Thanks for the bug report, I will look into that.  Shouldn't be too big of a fix.
Comment: I guess that means ... you get the open bounty of 500 reputation points! Congratulations! Go ahead and pick another problem, and in March 2019, you'll be able to get another 500 reputation points. Keep up the good work!
Comment: @nneonneo Fixed the bug: it didn't correctly reset the piece's column position after a failed collision check.  I've adjusted the score accordingly.
Comment: @PhiNotPi Should this CW answer be excluded from future bounties? Otherwise you will receive double since you have one of the other answers, too
Comment: How many GOL generations does this take per game tick? Game tick meaning the time between two possible inputs, the time it takes for a piece to fall one pixel or whatever defines the speed in this.
Comment: @Fabian See [this](https://chat.stackexchange.com/transcript/35837?m=39992040#39992040). Also [muddyfish = Blue] now.
Comment: So about 2*1000^6.
Comment: This is unfathomably awesome.
Comment: Holy cow! This may be the singular most impressive feat of computer engineering I've ever seen, surpassing some of the most outrageous things I've seen implemented in minecraft (which includes a working, and playable in real-time, copy of pokemon red)
Comment: "View in your browser" Haha very funny (it can't even do one step without hanging lol)
Answer: Part 2: OTCA Metapixel and VarLife
OTCA Metapixel

(Source)
The OTCA Metapixel is a construct in Conway's Game of Life that can be used to simulate any Life-like cellular automata. As the LifeWiki (linked above) says,

The OTCA metapixel is a 2048 × 2048 period 35328 unit cell that was constructed by Brice Due... It has many advantages... including the ability to emulate any Life-like cellular automaton and the fact that, when zoomed out, the ON and OFF cells are easy to distinguish...

What Life-like cellular automata means here is essentially that cells are born and cells survive according to how many of their eight neighbor cells are alive. The syntax for these rules is as follows: a B followed by the numbers of live neighbors that will cause a birth, then a slash, then an S followed by the numbers of live neighbors that will keep the cell alive. A bit wordy, so I think an example will help. The canonical Game of Life can be represented by the rule B3/S23, which says that any dead cell with three live neighbors will become alive and any live cell with two or three live neighbors will remain alive. Otherwise, the cell dies.
Despite being a 2048 x 2048 cell, the OTCA metapixel actually has a bounding box of 2058 x 2058 cells, the reason being that it overlaps by five cells in every direction with its diagonal neighbors. The overlapping cells serve to intercept gliders - which are emitted to signal the metacells neighbors that it's on - so that they don't interfere with other metapixels or fly off indefinitely. The birth and survival rules are encoded in a special section of cells at the left side of the metapixel, by the presence or absence of eaters in specific positions along two columns (one for birth, the other for survival). As for detecting the state of neighboring cells, here's how that happens:

A 9-LWSS stream then goes clockwise around the cell, losing a LWSS for each adjacent 'on' cell that triggered a honeybit reaction. The number of missing LWSSes is counted by detecting the position of the front LWSS by crashing another LWSS into it from the opposite direction. This collision releases gliders, which triggers another one or two honeybit reactions if the eaters that indicate that birth/survival condition are absent.

A more detailed diagram of each aspect of the OTCA metapixel can be found at its original website: How Does It Work?.
VarLife
I built an online simulator of Life-like rules where you could make any cell behave according to any life-like rule and called it "Variations of Life". This name has been shortened to "VarLife" to be more concise. Here's a screenshot of it and the link to it:

Notable features:

Toggle cells between live/dead and paint the board with different rules.
The ability to start and stop the simulation, and to do one step at a time. It's also possible to do a given number of steps as fast as possible or more slowly, at the rate set in the ticks-per-second and milliseconds-per-tick boxes.
Clear all live cells or to entirely reset the board to a blank state.
Can change the cell and board sizes, and also to enable toroidal wrapping horizontally and/or vertically.
Permalinks (which encode all information in the url) and short urls (because sometimes there's just too much info, but they're nice anyway).
Rule sets, with B/S specification, colors, and optional randomness.
And last but definitely not least, rendering gifs!

The render-to-gif feature is my favorite both because it took a ton of work to implement, so it was really satisfying when I finally cracked it at 7 in the morning, and because it makes it very easy to share VarLife constructs with others.
Basic VarLife Circuitry
All in all, the VarLife computer only needs four cell types! Eight states in all counting the dead/alive states. They are:

B/S (black/white), which serves as a buffer between all components since B/S cells can never be alive.
B1/S (blue/cyan), which is the main cell type used to propagate signals.
B2/S (green/yellow), which is mainly used for signal control, ensuring it doesn't backpropagate.
B12/S1 (red/orange), which is used in a few specialized situations, such as crossing signals and storing a bit of data.

Use this url to open up VarLife with these rules already encoded.
Wires
There are a few different wire designs with varying characteristics.
This is the easiest and most basic wire in VarLife, a strip of blue bordered by strips of green.

Short url: http://play.starmaninnovations.com/varlife/WcsGmjLiBF
This wire is unidirectional. That is, it will kill any signal attempting to travel in the opposite direction. It's also one cell narrower than the basic wire.

Short url
Diagonal wires also exist but they are not used much at all.

Short url
Gates
There are actually a lot of ways to construct each individual gate, so I will only be showing one example of each kind. This first gif demonstrates AND, XOR, and OR gates, respectively. The basic idea here is that a green cell acts like an AND, a blue cell acts like an XOR, and a red cell acts like an OR, and all the other cells around them are just there to control the flow properly.

Short url
The AND-NOT gate, abbreviated to "ANT gate", turned out to be a vital component. It is a gate that passes a signal from A if and only if there is no signal from B. Hence, "A AND NOT B".

Short url
While not exactly a gate, a wire crossing tile is still very important and useful to have.

Short url
Incidentally, there is no NOT gate here. That's because without an incoming signal, a constant output must be produced, which does not work well with the variety in timings that the current computer hardware requires. We got along just fine without it anyway.
Also, many components were intentionally designed to fit within an 11 by 11 bounding box (a tile) where it takes signals 11 ticks from entering the tile to leave the tile. This makes components more modular and easier to slap together as needed without having to worry about adjusting wires for either spacing or timing.
To see more gates that were discovered/constructed in the process of exploring circuitry components, check out this blog post by PhiNotPi: Building Blocks: Logic Gates.
Delay Components
In the process of designing the computer's hardware, KZhang devised multiple delay components, shown below.
4-tick delay:

Short url
5-tick delay:

Short url
8-tick delay (three different entry points):

Short url
11-tick delay:

Short url
12-tick delay:

Short url
14-tick delay:

Short url
15-tick delay (verified by comparing with this):

Short url
Well, that's it for basic circuitry components in VarLife! See KZhang's hardware post for the major circuitry of the computer!
Comment: VarLife is one of the most impressive parts of this project; it's versatility and simplicity compared to, for example, [Wireworld](https://en.wikipedia.org/wiki/Wireworld) is phenominal. The OTCA Metapixel does seem to be a lot larger than necessary though, have there been any attempts to golf it down?
Comment: Yeah, made a decent amount of progress this weekend on the heart of a 512x512 HashLife-friendly metacell ( http://conwaylife.com/forums/viewtopic.php?f=&p=51287#p51287 ).
The metacell could be made somewhat smaller, depending on how big a "pixel" area is wanted to signal the state of the cell when you're zoomed way out.
It definitely seems worth stopping at an exact 2^N-sized tile, though, because Golly's HashLife algorithm will be able run the  computer a whole lot faster.
Comment: Can't wires and gates be implemented in a less "wasteful" way? An electron would be represented by a glider or a spaceship (depending on the direction). I've seen arrangements that redirect them (and change from one to another if necessary) and some gates working with gliders. Yes, they take more space, the design is more complicated and the timing needs to be precise. But once you have those basic building blocks, they should be easy enough to put together and they would take a lot less space than VarLife implemented using OTCA. It would run faster, too.
Comment: @primo: Dave Greene is kinda working on that, it seems. https://chat.stackexchange.com/transcript/message/40106098#40106098
Comment: @Heimdall Something like this? https://www.nicolasloizeau.com/gol-computer
Comment: @Heimdall Although that would work well, it would not show well while playing Tetris.
Comment: @tzot Yes! Of course, gates can be implemented in other ways, too. Also the basic glider moves diagonally but you can change it into a spaceship and back. But I guess that doesn't help much. More importantly, a screen should be implemented (I'm imagining something similar to the metapixel, but without structures to check neighbours, and triggering it would be done by sending a glider into a particular part of it), and also an input device where deleting a certain glider would count as a certain button press.
Comment: most of the links still work via web.archive.org
Answer: Part 3: Hardware
With our knowledge of logic gates and the general structure of the processor, we can start designing all the components of the computer.
Demultiplexer
A demultiplexer, or demux, is a crucial component to the ROM, RAM, and ALU.
It routes an input signal to one of the many output signals based on some given selector data.
It is composed of 3 main parts: a serial to parallel converter, a signal checker and a clock signal splitter.
We start by converting the serial selector data to "parallel".
This is done by strategically splitting and delaying the data so that the leftmost bit of data intersects the clock signal at the leftmost 11x11 square, the next bit of data intersects the clock signal at the next 11x11 square, and so on.
Although every bit of data will be outputted in every 11x11 square, every bit of data will intersect with the clock signal only once.

Next, we will check to see if the parallel data matches a preset address.
We do this by using AND and ANT gates on the clock and parallel data.
However, we need to make sure that the parallel data is also outputted so that it can be compared again.
These are the gates that I came up with:

Finally, we just split the clock signal, stack a bunch of signal checkers (one for each address/output) and we have a multiplexer!

ROM
The ROM is supposed to take an address as an input and send out the instruction at that address as its output.
We start by using a multiplexer to direct the clock signal to one of the instructions.
Next, we need to generate a signal using some wire crossings and OR gates.
The wire crossings enable the clock signal to travel down all 58 bits of the instruction, and also allow for a generated signal (currently in parallel) to move down through the ROM to be outputted.

Next we just need to convert the parallel signal to serial data, and the ROM is complete.

The ROM is currently generated by running a script in Golly that will translate assembly code from your clipboard into ROM.
SRL, SL, SRA
These three logic gates are used for bit shifts, and they are more complicated than your typical AND, OR, XOR, etc.
To make these gates work, we will first delay the clock signal an appropriate amount of time to cause a "shift" in the data.
The second argument given to these gates dictates how many bits to shift.
For the SL and the SRL, we need to

Make sure that the 12 most significant bits are not on (otherwise the output is simply 0), and
Delay the data the correct amount based on the 4 least significant bits.

This is doable with a bunch of AND/ANT gates and a multiplexer.

The SRA is slightly different, because we need to copy the sign bit during the shift.
We do this by ANDing the clock signal with the sign bit, and then copy that output a bunch of times with wire splitters and OR gates.

Set-Reset (SR) latch
Many portions of the processor's functionality rely on the ability to store data.
Using 2 red B12/S1 cells, we can do just that.
The two cells can keep each other on, and can also stay off together.
Using some extra set, reset, and read circuitry, we can make a simple SR latch.

Synchronizer
By converting serial data to parallel data, then setting a bunch of SR latches, we can store a whole word of data.
Then, to get the data out again, we can just read and reset all of the latches, and delay the data accordingly.
This enables us to store one (or more) word of data while waiting for another, allowing for two words of data arriving at different times to be synchronized.

Read Counter
This device keeps track of how many more times it needs to address from RAM.
It does this using a device similar to the SR latch: a T flip flop.
Every time the T flip flop recieves an input, it changes state: if it was on, it turns off, and vice versa.
When the T flip flop is flipped from on to off, it sends out an output pulse, which can be fed into another T flip flop to form a 2 bit counter.

In order to make the Read Counter, we need to set the counter to the appropriate addressing mode with two ANT gates, and use the counter's output signal to decide where to direct the clock signal: to the ALU or to the RAM.

Read Queue
The read queue needs to keep track of which read counter sent an input to RAM, so that it can send the RAM's output to the correct location.
To do that, we use some SR latches: one latch for each input.
When a signal is sent to RAM from a read counter, the clock signal is split and sets the counter's SR latch.
The RAM's output is then ANDed with the SR latch, and the clock signal from the RAM resets the SR latch.

ALU
The ALU functions similarly to the read queue, in that it uses an SR latch to keep track of where to send a signal.
First, the SR latch of the logic circuit corresponding to the opcode of the instruction is set using a multiplexer.
Next, the first and second argument's values are ANDed with the SR latch, and then are passed to the logic circuits.
The clock signal resets the latch as it's passing so that the ALU can be used again.
(Most of the circuitry is golfed down, and a ton of delay management is shoved in, so it looks like a bit of a mess)

RAM
The RAM was the most complicated part of this project.
It required for very specific control over each SR latch that stored data.
For reading, the address is sent into a multiplexer and sent to the RAM units.
The RAM units output the data they store in parallel, which is converted to serial and outputted.
For writing, the address is sent into a different multiplexer, the data to be written is converted from serial to parallel, and the RAM units propagate the signal throughout the RAM.
Each 22x22 metapixel RAM unit has this basic structure:

Putting the whole RAM together, we get something that looks like this:

Putting everything together
Using all of these components and the general computer architecture described in the Overview, we can construct a working computer!
Downloads:
- Finished Tetris computer
- ROM creation script, empty computer, and prime finding computer
Comment: I would just like to say that the images in this post are, for whatever reason, very beautiful in my opinion. :P +1
Comment: Is this processor vulnerable for the Spectre and Meltdown attack? :)
Comment: This is the most amazing thing I have ever seen.... I would +20 if I could
Comment: @Ferrybig no branch prediction, so I doubt it.
Comment: @tfbninja You can, that's called a bounty and you can give 200 reputation.
Comment: Help! all of the images were Bonked!
Comment: One of the "011"s in the picture above "The ROM is currently…" is meant to be "111", right?
Comment: @Fabian I double checked all of the labels in that picture, and they should all be correct. The labels describe what data is at a ROM location, and so it is okay for 2 different addresses to have the same data.
Comment: The images don't show up
Comment: beautiful (why does it look like minecraft hehe)
Answer: Part 4: QFTASM and Cogol
Architecture Overview
In short, our computer has a 16-bit asynchronous RISC Harvard architecture. When building a processor by hand, a RISC (reduced instruction set computer) architecture is practically a requirement. In our case, this means that the number of opcodes is small and, much more importantly, that all instructions are processed in a very similar manner.
For reference, the Wireworld computer used a transport-triggered architecture, in which the only instruction was MOV and computations were performed by writing/reading special registers. Although this paradigm leads to a very easy-to-implement architecture, the result is also borderline unusable: all arithmetic/logic/conditional operations require three instructions. It was clear to us that we wanted to create a much less esoteric architecture.
In order to keep our processor simple while increasing usability, we made several important design decisions:

No registers. Every address in RAM is treated equally and can be used as any argument for any operation. In a sense, this means all of RAM could be treated like registers. This means that there are no special load/store instructions.
In a similar vein, memory-mapping. Everything that could be written to or read from shares a unified addressing scheme. This means that the program counter (PC) is address 0, and the only difference between regular instructions and control-flow instructions is that control-flow instructions use address 0.
Data is serial in transmission, parallel in storage. Due to the "electron"-based nature of our computer, addition and subtraction are significantly easier to implement when the data is transmitted in serial little-endian (least-significant bit first) form. Furthermore, serial data removes the need for cumbersome data buses, which are both really wide and cumbersome to time properly (in order for the data to stay together, all "lanes" of the bus must experience the same travel delay).
Harvard architecture, meaning a division between program memory (ROM) and data memory (RAM). Although this does reduce the flexibility of the processor, this helps with size optimization: the length of the program is much larger than the amount of RAM we'll need, so we can split the program off into ROM and then focus on compressing the ROM, which is much easier when it is read-only.
16-bit data width. This is the smallest power of two that is wider than a standard Tetris board (10 blocks). This gives us a data range of -32768 to +32767 and a maximum program length of 65536 instructions. (2^8=256 instructions is enough for most simple things we might want a toy processor to do, but not Tetris.)
Asynchronous design. Rather than having a central clock (or, equivalently, several clocks) dictating the timing of the computer, all data is accompanied by a "clock signal" which travels in parallel with the data as it flows around the computer. Certain paths may be shorter than others, and while this would pose difficulties for a centrally-clocked design, an asynchronous design can easily deal with variable-time operations.
All instructions are of equal size. We felt that an architecture in which each instruction has 1 opcode with 3 operands (value value destination) was the most flexible option. This encompasses binary data operations as well as conditional moves.
Simple addressing mode system. Having a variety of addressing modes is very useful for supporting things such as arrays or recursion. We managed to implement several important addressing modes with a relatively simple system.

An illustration of our architecture is contained in the overview post.
Functionality and ALU Operations
From here, it was a matter of determining what functionality our processor should have. Special attention was paid to the ease of implementation as well as the versatility of each command.
Conditional Moves
Conditional moves are very important and serve as both small-scale and large-scale control flow. "Small-scale" refers to its ability to control the execution of a particular data move, while "large-scale" refers to its use as a conditional jump operation to transfer control flow to any arbitrary piece of code. There are no dedicated jump operations because, due to memory mapping, a conditional move can both copy data to regular RAM and copy a destination address to the PC. We also chose to forgo both unconditional moves and unconditional jumps for a similar reason: both can be implemented as a conditional move with a condition that's hardcoded to TRUE.
We chose to have two different types of conditional moves: "move if not zero" (MNZ) and "move if less than zero" (MLZ). Functionally, MNZ amounts to checking whether any bit in the data is a 1, while MLZ amounts to checking if the sign bit is 1. They are useful for equalities and comparisons, respectively. The reason we chose these two over others such as "move if zero" (MEZ) or "move if greater than zero" (MGZ) was that MEZ would require creating a TRUE signal from an empty signal, while MGZ is a more complex check, requiring the the sign bit be 0 while at least one other bit be 1.
Arithmetic
The next-most important instructions, in terms of guiding the processor design, are the basic arithmetic operations. As I mentioned earlier, we are using little-endian serial data, with the choice of endianness determined by the ease of addition/subtraction operations. By having the least-significant bit arrive first, the arithmetic units can easily keep track of the carry bit.
We chose to use 2's complement representation for negative numbers, since this makes addition and subtraction more consistent. It's worth noting that the Wireworld computer used 1's complement.
Addition and subtraction are the extent of our computer's native arithmetic support (besides bit shifts which are discussed later). Other operations, like multiplication, are far too complex to be handled by our architecture, and must be implemented in software.
Bitwise Operations
Our processor has AND, OR, and XOR instructions which do what you would expect. Rather than have a NOT instruction, we chose to have an "and-not" (ANT) instruction. The difficulty with the NOT instruction is again that it must create signal from a lack of signal, which is difficult with a cellular automata. The ANT instruction returns 1 only if the first argument bit is 1 and the second argument bit is 0. Thus, NOT x is equivalent to ANT -1 x (as well as XOR -1 x). Furthermore, ANT is versatile and has its main advantage in masking: in the case of the Tetris program we use it to erase tetrominoes.
Bit Shifting
The bit-shifting operations are the most complex operations handled by the ALU. They take two data inputs: a value to shift and an amount to shift it by. Despite their complexity (due to the variable amount of shifting), these operations are crucial for many important tasks, including the many "graphical" operations involved in Tetris. Bit shifts would also serve as the foundation for efficient multiplication/division algorithms.
Our processor has three bit shift operations, "shift left" (SL), "shift right logical" (SRL), and "shift right arithmetic" (SRA). The first two bit shifts (SL and SRL) fill in the new bits with all zeros (meaning that a negative number shifted right will no longer be negative). If the second argument of the shift is outside the range of 0 to 15, the result is all zeros, as you might expect. For the last bit shift, SRA, the bit shift preserves the sign of the input, and therefore acts as a true division by two.
Instruction Pipelining
Now's the time to talk about some of the gritty details of the architecture. Each CPU cycle consists of the following five steps:
1. Fetch the current instruction from ROM
The current value of the PC is used to fetch the corresponding instruction from ROM. Each instruction has one opcode and three operands. Each operand consists of one data word and one addressing mode. These parts are split from each other as they are read from the ROM.
The opcode is 4 bits to support 16 unique opcodes, of which 11 are assigned:
0000  MNZ    Move if Not Zero
0001  MLZ    Move if Less than Zero
0010  ADD    ADDition
0011  SUB    SUBtraction
0100  AND    bitwise AND
0101  OR     bitwise OR
0110  XOR    bitwise eXclusive OR
0111  ANT    bitwise And-NoT
1000  SL     Shift Left
1001  SRL    Shift Right Logical
1010  SRA    Shift Right Arithmetic
1011  unassigned
1100  unassigned
1101  unassigned
1110  unassigned
1111  unassigned

2. Write the result (if necessary) of the previous instruction to RAM
Depending on the condition of the previous instruction (such as the value of the first argument for a conditional move), a write is performed. The address of the write is determined by the third operand of the previous instruction.
It is important to note that writing occurs after instruction fetching. This leads to the creation of a branch delay slot in which the instruction immediately after a branch instruction (any operation which writes to the PC) is executed in lieu of the first instruction at the branch target.
In certain instances (like unconditional jumps), the branch delay slot can be optimized away. In other cases it cannot, and the instruction after a branch must be left empty. Furthermore, this type of delay slot means that branches must use a branch target that is 1 address less than the actual target instruction, to account for the PC increment that occurs.
In short, because the previous instruction's output is written to RAM after the next instruction is fetched, conditional jumps need to have a blank instruction after them, or else the PC won't be updated properly for the jump.
3. Read the data for the current instruction's arguments from RAM
As mentioned earlier, each of the three operands consists of both a data word and an addressing mode. The data word is 16 bits, the same width as RAM. The addressing mode is 2 bits.
Addressing modes can be a source of significant complexity for a processor like this, as many real-world addressing modes involve multi-step computations (like adding offsets). At the same time, versatile addressing modes play an important role in the usability of the processor.
We sought to unify the concepts of using hard-coded numbers as operands and using data addresses as operands. This led to the creation of counter-based addressing modes: the addressing mode of an operand is simply a number representing how many times the data should be sent around a RAM read loop. This encompasses immediate, direct, indirect, and double-indirect addressing.
00  Immediate:  A hard-coded value. (no RAM reads)
01  Direct:  Read data from this RAM address. (one RAM read)
10  Indirect:  Read data from the address given at this address. (two RAM reads)
11  Double-indirect: Read data from the address given at the address given by this address. (three RAM reads)

After this dereferencing is performed, the three operands of the instruction have different roles. The first operand is usually the first argument for a binary operator, but also serves as the condition when the current instruction is a conditional move. The second operand serves as the second argument for a binary operator. The third operand serves as the destination address for the result of the instruction.
Since the first two instructions serve as data while the third serves as an address, the addressing modes have slightly different interpretations depending on which position they are used in. For example, the direct mode is used to read data from a fixed RAM address (since one RAM read is needed), but the immediate mode is used to write data to a fixed RAM address (since no RAM reads are necessary).
4. Compute the result
The opcode and the first two operands are sent to the ALU to perform a binary operation. For the arithmetic, bitwise, and shift operations, this means performing the relevant operation. For the conditional moves, this means simply returning the second operand.
The opcode and first operand are used to compute the condition, which determines whether or not to write the result to memory. In the case of conditional moves, this means either determining whether any bit in the operand is 1 (for MNZ), or determining whether the sign bit is 1 (for MLZ). If the opcode isn't a conditional move, then write is always performed (the condition is always true).
5. Increment the program counter
Finally, the program counter is read, incremented, and written.
Due to the position of the PC increment between the instruction read and the instruction write, this means that an instruction which increments the PC by 1 is a no-op. An instruction that copies the PC to itself causes the next instruction to be executed twice in a row. But, be warned, multiple PC instructions in a row can cause complex effects, including infinite looping, if you don't pay attention to the instruction pipeline.
Quest for Tetris Assembly
We created a new assembly language named QFTASM for our processor. This assembly language corresponds 1-to-1 with the machine code in the computer's ROM.
Any QFTASM program is written as a series of instructions, one per line. Each line is formatted like this:
[line numbering] [opcode] [arg1] [arg2] [arg3]; [optional comment]

Opcode List
As discussed earlier, there are eleven opcodes supported by the computer, each of which have three operands:
MNZ [test] [value] [dest]  – Move if Not Zero; sets [dest] to [value] if [test] is not zero.
MLZ [test] [value] [dest]  – Move if Less than Zero; sets [dest] to [value] if [test] is less than zero.
ADD [val1] [val2] [dest]   – ADDition; store [val1] + [val2] in [dest].
SUB [val1] [val2] [dest]   – SUBtraction; store [val1] - [val2] in [dest].
AND [val1] [val2] [dest]   – bitwise AND; store [val1] & [val2] in [dest].
OR [val1] [val2] [dest]    – bitwise OR; store [val1] | [val2] in [dest].
XOR [val1] [val2] [dest]   – bitwise XOR; store [val1] ^ [val2] in [dest].
ANT [val1] [val2] [dest]   – bitwise And-NoT; store [val1] & (![val2]) in [dest].
SL [val1] [val2] [dest]    – Shift Left; store [val1] << [val2] in [dest].
SRL [val1] [val2] [dest]   – Shift Right Logical; store [val1] >>> [val2] in [dest]. Doesn't preserve sign.
SRA [val1] [val2] [dest]   – Shift Right Arithmetic; store [val1] >> [val2] in [dest], while preserving sign.

Addressing Modes
Each of the operands contains both a data value and an addressing move. The data value is described by a decimal number in the range -32768 to 32767. The addressing mode is described by a one-letter prefix to the data value.
mode    name               prefix
0       immediate          (none)
1       direct             A
2       indirect           B
3       double-indirect    C

Example Code
Fibonacci sequence in five lines:
0. MLZ -1 1 1;    initial value
1. MLZ -1 A2 3;   start loop, shift data
2. MLZ -1 A1 2;   shift data
3. MLZ -1 0 0;    end loop
4. ADD A2 A3 1;   branch delay slot, compute next term

This code computes the Fibonacci sequence, with RAM address 1 containing the current term. It quickly overflows after 28657.
Gray code:
0. MLZ -1 5 1;      initial value for RAM address to write to
1. SUB A1 5 2;      start loop, determine what binary number to covert to Gray code
2. SRL A2 1 3;      shift right by 1
3. XOR A2 A3 A1;    XOR and store Gray code in destination address
4. SUB B1 42 4;     take the Gray code and subtract 42 (101010)
5. MNZ A4 0 0;      if the result is not zero (Gray code != 101010) repeat loop
6. ADD A1 1 1;      branch delay slot, increment destination address

This program computes Gray code and stores the code in succesive addresses starting at address 5. This program utilizes several important features such as indirect addressing and a conditional jump. It halts once the resultant Gray code is 101010, which happens for input 51 at address 56.
Online Interpreter
El'endia Starman has created a very useful online interpreter here. You are able to step through the code, set breakpoints, perform manual writes to RAM, and visualize the RAM as a display.
Cogol
Once the architecture and assembly language were defined, the next step on the "software" side of the project was the creation of a higher-level language, something suitable for Tetris. Thus I created Cogol. The name is both a pun on "COBOL" and an acronym for "C of Game of Life", although it is worth noting that Cogol is to C what our computer is to an actual computer.
Cogol exists at a level just above assembly language. Generally, most lines in a Cogol program each correspond to a single line of assembly, but there are some important features of the language:

Basic features include named variables with assignments and operators that have more readable syntax. For example, ADD A1 A2 3 becomes z = x + y;, with the compiler mapping variables onto addresses.
Looping constructs such as if(){}, while(){}, and do{}while(); so the compiler handles branching.
One-dimensional arrays (with pointer arithmetic), which are used for the Tetris board.
Subroutines and a call stack. These are useful for preventing duplication of large chunks of code, and for supporting recursion.

The compiler (which I wrote from scratch) is very basic/naive, but I've attempted to hand-optimize several of the language constructs to achieve a short compiled program length.
Here are some short overviews of how various language features work:
Tokenization
The source code is tokenized linearly (single-pass), using simple rules about which characters are allowed to be adjacent within a token.  When a character is encountered that cannot be adjacent to the last character of the current token, the current token is deemed complete and the new character begins a new token.  Some characters (such as { or ,) cannot be adjacent to any other characters and are therefore their own token.  Others (like > or =) are only allowed to be adjacent to other characters within their class, and can thus form tokens like >>>, ==, or >=, but not like =2.  Whitespace characters force a boundary between tokens but aren't themselves included in the result.  The most difficult character to tokenize is - because it can both represent subtraction and unary negation, and thus requires some special-casing.
Parsing
Parsing is also done in a single-pass fashion.  The compiler has methods for handling each of the different language constructs, and tokens are popped off of the global token list as they are consumed by the various compiler methods.  If the compiler ever sees a token that it does not expect, it raises a syntax error.
Global Memory Allocation
The compiler assigns each global variable (word or array) its own designated RAM address(es).  It is necessary to declare all variables using the keyword my so that the compiler knows to allocate space for it.  Much cooler than named global variables is the scratch address memory management.  Many instructions (notably conditionals and many array accesses) require temporary "scratch" addresses to store intermediate calculations.  During the compilation process the compiler allocates and de-allocates scratch addresses as necessary.  If the compiler needs more scratch addresses, it will dedicate more RAM as scratch addresses.  I believe it's typical for a program to only require a few scratch addresses, although each scratch address will be used many times.
IF-ELSE Statements
The syntax for if-else statements is the standard C form:
other code
if (cond) {
  first body
} else {
  second body
}
other code

When converted to QFTASM, the code is arranged like this:
other code
condition test
conditional jump
first body
unconditional jump
second body (conditional jump target)
other code (unconditional jump target)

If the first body is executed, the second body is skipped over.  If the first body is skipped over, the second body is executed.
In the assembly, a condition test is usually just a subtraction, and the sign of the result determines whether to make the jump or execute the body.  An MLZ instruction is used to handle inequalities such as > or <=.  An MNZ instruction is used to handle ==, since it jumps over the body when the difference is not zero (and therefore when the arguments are not equal).  Multi-expression conditionals are not currently supported.
If the else statement is omitted, the unconditional jump is also omitted, and the QFTASM code looks like this:
other code
condition test
conditional jump
body
other code (conditional jump target)

WHILE Statements
The syntax for while statements is also the standard C form:
other code
while (cond) {
  body
}
other code

When converted to QFTASM, the code is arranged like this:
other code
unconditional jump
body (conditional jump target)
condition test (unconditional jump target)
conditional jump
other code

The condition testing and conditional jump are at the end of the block, which means they are re-executed after each execution of the block.  When the condition is returns false the body is not repeated and the loop ends.  During the start of loop execution, control flow jumps over the loop body to the condition code, so the body is never executed if the condition is false the first time.
An MLZ instruction is used to handle inequalities such as > or <=.  Unlike during if statements, an MNZ instruction is used to handle !=, since it jumps to the body when the difference is not zero (and therefore when the arguments are not equal).
DO-WHILE Statements
The only difference between while and do-while is that the a do-while loop body is not initially skipped over so it is always executed at least once.  I generally use do-while statements to save a couple lines of assembly code when I know the loop will never need to be skipped entirely.
Arrays
One-dimensional arrays are implemented as contiguous blocks of memory.  All arrays are fixed-length based on their declaration.  Arrays are declared like so:
my alpha[3];               # empty array
my beta[11] = {3,2,7,8};   # first four elements are pre-loaded with those values

For the array, this is a possible RAM mapping, showing how addresses 15-18 are reserved for the array:
15: alpha
16: alpha[0]
17: alpha[1]
18: alpha[2]

The address labeled alpha is filled with a pointer to the location of alpha[0], so in thie case address 15 contains the value 16.  The alpha variable can be used inside of the Cogol code, possibly as a stack pointer if you want to use this array as a stack.
Accessing the elements of an array is done with the standard array[index] notation.  If the value of index is a constant, this reference is automatically filled in with the absolute address of that element.  Otherwise it performs some pointer arithmetic (just addition) to find the desired absolute address.  It is also possible to nest indexing, such as alpha[beta[1]].
Subroutines and Calling
Subroutines are blocks of code that can be called from multiple contexts, preventing duplication of code and allowing for the creation of recursive programs.  Here is a program with a recursive subroutine to generate Fibonacci numbers (basically the slowest algorithm):
# recursively calculate the 10th Fibonacci number
call display = fib(10).sum;
sub fib(cur,sum) {
  if (cur <= 2) {
    sum = 1;
    return;
  }
  cur--;
  call sum = fib(cur).sum;
  cur--;
  call sum += fib(cur).sum;
}

A subroutine is declared with the keyword sub, and a subroutine can be placed anywhere inside the program.  Each subroutine can have multiple local variables, which are declared as part of its list of arguments.  These arguments can also be given default values.
In order to handle recursive calls, the local variables of a subroutine are stored on the stack.  The last static variable in RAM is the call stack pointer, and all memory after that serves as the call stack.  When a subroutine is called, it created a new frame on the call stack, which includes all local variables as well as the return (ROM) address.  Each subroutine in the program is given a single static RAM address to serve as a pointer.  This pointer gives the location of the "current" call of the subroutine in the call stack.  Referencing a local variable is done using the value of this static pointer plus an offset to give the address of that particular local variable.  Also contained in the call stack is the previous value of the static pointer.  Here's the variables mapping of both the static RAM and the subroutine call frame for the above program:
RAM map:
0: pc
1: display
2: scratch0
3: fib
4: scratch1
5: scratch2
6: scratch3
7: call

fib map:
0: return
1: previous_call
2: cur
3: sum

One thing that is interesting about subroutines is that they do not return any particular value.  Rather, all of the local variables of the subroutine can be read after the subroutine is performed, so a variety of data can be extracted from a subroutine call.  This is accomplished by storing the pointer for that specific call of the subroutine, which can then be used to recover any of the local variables from within the (recently-deallocated) stack frame.
There are multiple ways to call a subroutine, all using the call keyword:
call fib(10);   # subroutine is executed, no return vaue is stored

call pointer = fib(10);   # execute subroutine and return a pointer
display = pointer.sum;    # access a local variable and assign it to a global variable

call display = fib(10).sum;   # immediately store a return value

call display += fib(10).sum;   # other types of assignment operators can also be used with a return value

Any number of values can be given as arguments for a subroutine call.  Any argument not provided will be filled in with its default value, if any.  An argument that is not provided and has no default value is not cleared (to save instructions/time) so could potentially take on any value at the start of the subroutine.
Pointers are a way of accessing multiple local variables of subroutine, although it is important to note that the pointer is only temporary: the data the pointer points to will be destroyed when another subroutine call is made.
Debugging Labels
Any {...} code block in a Cogol program can be preceded by a multi-word descriptive label.  This label is attached as a comment in the compiled assembly code, and can be very useful for debugging since it makes it easier to locate specific chunks of code.
Branch Delay Slot Optimization
In order to improve the speed of the compiled code, the Cogol compiler performs some really basic delay slot optimization as a final pass over the QFTASM code.  For any unconditional jump with an empty branch delay slot, the delay slot can be filled by the first instruction at the jump destination, and the jump destination is incremented by one to point to the next instruction.  This generally saves one cycle each time an unconditional jump is performed.
Writing the Tetris code in Cogol
The final Tetris program was written in Cogol, and the source code is available here.  The compiled QFTASM code is available here.  For convenience, a permalink is provided here: Tetris in QFTASM.  Since the goal was to golf the assembly code (not the Cogol code), the resultant Cogol code is unwieldy.  Many portions of the program would normally be located in subroutines, but those subroutines were actually short enough that duplicating the code saved instructions over the call statements.  The final code only has one subroutine in addition to the main code.  Additionally, many arrays were removed and replaced either with an equivalently-long list of individual variables, or by a lot of hard-coded numbers in the program.  The final compiled QFTASM code is under 300 instructions, although it is only slightly longer than the Cogol source itself.
Comment: I love that the choice of assembly language instructions is defined by your substrate hardware (no MEZ because assembling a true from two falses is hard). Fantastic read.
Comment: You said that `=` can only stand next to itself, but there's a `!=`.
Comment: @Fabian *and* a `+=`
Comment: @Oliphaunt Yeah my description wasn't quite accurate, it's more of a character-class thing, where a certain class of characters can be adjacent to each other.
Answer: Part 5: Assembly, Translation, and the Future
With our assembly program from the compiler, it's time to assemble a ROM for the Varlife computer, and translate everything into a big GoL pattern!
Assembly
Assembling the assembly program into a ROM is done in much the same way as in traditional programming: each instruction is translated into a binary equivalent, and those are then concatenated into a large binary blob that we call an executable. For us, the only difference is, that binary blob needs to be translated into Varlife circuits and attached to the computer.
K Zhang wrote CreateROM.py, a Python script for Golly that does the assembly and translation. It's fairly straightforward: it takes an assembly program from the clipboard, assembles it into a binary, and translates that binary into circuitry. Here's an example with a simple primality tester included with the script:
#0. MLZ -1 3 3;
#1. MLZ -1 7 6; preloadCallStack
#2. MLZ -1 2 1; beginDoWhile0_infinite_loop
#3. MLZ -1 1 4; beginDoWhile1_trials
#4. ADD A4 2 4;
#5. MLZ -1 A3 5; beginDoWhile2_repeated_subtraction
#6. SUB A5 A4 5;
#7. SUB 0 A5 2;
#8. MLZ A2 5 0;
#9. MLZ 0 0 0; endDoWhile2_repeated_subtraction
#10. MLZ A5 3 0;
#11. MNZ 0 0 0; endDoWhile1_trials
#12. SUB A4 A3 2;
#13. MNZ A2 15 0; beginIf3_prime_found
#14. MNZ 0 0 0;
#15. MLZ -1 A3 1; endIf3_prime_found
#16. ADD A3 2 3;
#17. MLZ -1 3 0;
#18. MLZ -1 1 4; endDoWhile0_infinite_loop

This produces the following binary:
0000000000000001000000000000000000010011111111111111110001
0000000000000000000000000000000000110011111111111111110001
0000000000000000110000000000000000100100000000000000110010
0000000000000000010100000000000000110011111111111111110001
0000000000000000000000000000000000000000000000000000000000
0000000000000000000000000000000011110100000000000000100000
0000000000000000100100000000000000110100000000000001000011
0000000000000000000000000000000000000000000000000000000000
0000000000000000000000000000000000110100000000000001010001
0000000000000000000000000000000000000000000000000000000001
0000000000000000000000000000000001010100000000000000100001
0000000000000000100100000000000001010000000000000000000011
0000000000000001010100000000000001000100000000000001010011
0000000000000001010100000000000000110011111111111111110001
0000000000000001000000000000000000100100000000000001000010
0000000000000001000000000000000000010011111111111111110001
0000000000000000010000000000000000100011111111111111110001
0000000000000001100000000000000001110011111111111111110001
0000000000000000110000000000000000110011111111111111110001

When translated to Varlife circuits, it looks like this:

The ROM is then linked up with the computer, which forms a fully functioning program in Varlife. But we're not done yet...
Translation to Game of Life
This whole time, we've been working in various layers of abstraction above the base of Game of Life. But now, it's time to pull back the curtain of abstraction and translate our work into a Game of Life pattern. As previously mentioned, we are using the OTCA Metapixel as the base for Varlife. So, the final step is to convert each cell in Varlife to a metapixel in Game of Life.
Thankfully, Golly comes with a script (metafier.py) that can convert patterns in different rulesets to Game of Life patterns via the OTCA Metapixel. Unfortunately, it is only designed to convert patterns with a single global ruleset, so it doesn't work on Varlife. I wrote a modified version that addresses that issue, so that the rule for each metapixel is generated on a cell-by-cell basis for Varlife.
So, our computer (with the Tetris ROM) has a bounding box of 1,436 x 5,082. Of the 7,297,752 cells in that box, 6,075,811 are empty space, leaving an actual population count of 1,221,941. Each of those cells needs to be translated into an OTCA metapixel, which has a bounding box of 2048x2048 and a population of either 64,691 (for an ON metapixel) or 23,920 (for an OFF metapixel). That means the final product will have a bounding box of 2,940,928 x 10,407,936 (plus a few thousand extra for the borders of the metapixels), with a population between 29,228,828,720 and 79,048,585,231. With 1 bit per live cell, that's between 27 and 74 GiB needed to represent the entire computer and ROM.
I included those calculations here because I neglected to run them before starting the script, and very quickly ran out of memory on my computer. After a panicked kill command, I made a modification to the metafier script. Every 10 lines of metapixels, the pattern is saved to disk (as a gzipped RLE file), and the grid is flushed. This adds extra runtime to the translation and uses more disk space, but keeps memory usage within acceptable limits. Because Golly uses an extended RLE format that includes the location of the pattern, this doesn't add any more complexity to the loading of the pattern - just open all of the pattern files on the same layer.
K Zhang built off of this work, and created a more efficient metafier script that utilizes the MacroCell file format, which is loads more efficient than RLE for large patterns. This script runs considerably faster (a few seconds, compared to multiple hours for the original metafier script), creates vastly smaller output (121 KB versus 1.7 GB), and can metafy the entire computer and ROM in one fell swoop without using a massive amount of memory. It takes advantage of the fact that MacroCell files encode trees that describe the patterns. By using a custom template file, the metapixels are pre-loaded into the tree, and after some computations and modifications for neighbor detection, the Varlife pattern can simply be appended.
The pattern file of the entire computer and ROM in Game of Life can be found here.

The Future of the Project
Now that we've made Tetris, we're done, right? Not even close. We have several more goals for this project that we are working towards:

muddyfish and Kritixi Lithos are continuing work on the higher-level language that compiles to QFTASM.
El'endia Starman is working on upgrades to the online QFTASM interpreter.
quartata is working on a GCC backend, which will allow compilation of freestanding C and C++ code (and potentially other languages, like Fortran, D, or Objective-C) into QFTASM via GCC. This will allow for more sophisticated programs to be created in a more familiar language, albeit without a standard library.
One of the biggest hurdles that we have to overcome before we can make more progress is the fact that our tools can't emit position-independent code (e.g. relative jumps). Without PIC, we can't do any linking, and so we miss out on the advantages that come from being able to link to existing libraries. We're working on trying to find a way to do PIC correctly.
We are discussing the next program that we want to write for the QFT computer. Right now, Pong looks like a nice goal.
Comment: The next program you write for it should be Conway's Game of Life.
Comment: Do you have video of it running?
Comment: @ACK_stoverflow That's going to be done at some point.
Comment: A native COGOL compiler is another must-implement.
Comment: @Timmmm Yes, but very slowly. (You also have to use HashLife).
Comment: Just looking at the future subsection, isn't a relative jump just an `ADD PC offset PC`?  Excuse my naivete if this is incorrect, assembly programming never was my forte.
Comment: So... can Golly actually run it?
Comment: @Joe We would have to emulate a VGA display for that, which is not worth the effort. Alternatively we could colorize the online display, but that is also probably not worth the effort either.
Comment: @MBraedley That's what a relative jump looks like, but currently we have no way of using the current value of the PC as a jump offset. There are also some more complications involving writing PIC that quartata is probably more capable of explaining.
Comment: @ACK_stoverflow CGOL in CGOL has already been done, but it would still be impressive to see it again, I guess...
Comment: Two words: color display.
Comment: @Mego That's amazing.
Comment: Linking can be done without PIC, but it's more work.  Probably better get PIC than to make the more complex library format & linker that would be needed to do without it.
Comment: @quartata Perhaps the https://github.com/shinh/elvm backend would be easier to use than gcc's? Its only frontend is C, but it is supposedly much easier to use.
Comment: The game field is not really visible, because when a game pixel is on, that just means that a few metapixels are on, which make a really small difference in the look of the RAM bit. And you have to see hundreds of bits in RAM to see the playing field. Couldn't that be solved with meta-meta-pixels?
Comment: @noɥʇʎԀʎzɐɹƆ , I think directly targeting LLVM would be easier.
Comment: How does the one-dimensional assembly code get mapped to two-dimensional meta-pixel-space?
Comment: are there any updates about the current state of the compilation from C to QFTASM?
Answer: Part 6: The Newer Compiler to QFTASM
Although Cogol is sufficient for a rudimentary Tetris implementation, it is too simple and too low-level for general-purpose programming at an easily readable level.
We began work on a new language in September 2016.
Progress on the language was slow due to hard to understand bugs as well as real life.
We built a low level language with similar syntax to Python, including a simple type system, subroutines supporting recursion and inline operators.
The compiler from text to QFTASM was created with 4 steps: the tokeniser, the grammar tree, a high level compiler and a low level compiler.
The tokeniser
Development was started using Python using the built in tokeniser library, meaning this step was pretty simple.
Only a few changes to the default output were required, including stripping comments (but not #includes).
The grammar tree
The grammar tree was created to be easily extendible without having to modify any source code.
The tree structure is stored in an XML file which includes the structure of the nodes that can make up the tree and how they're made up with other nodes and tokens.
The grammar needed to support repeated nodes as well as optional ones. This was achieved by introducing meta tags to describe how tokens were to be read.
The tokens that are generated then get parsed through the rules of the grammar such that the output forms a tree of grammar elements such as subs and generic_variables, which in turn contain other grammar elements and tokens.
Compilation into high level code
Each feature of the language needs to be able to be compiled into high level constructs. These include assign(a, 12)
 and call_subroutine(is_prime, call_variable=12, return_variable=temp_var). Features such as the inlining of elements are executed in this segment. These are defined as operators and are special in that they're inlined every time an operator such as + or % are used. Because of this, they're more restricted than regular code - they can't use their own operator nor any operator that relies on the one being defined.
During the inlining process, the internal variables are replaced with the ones being called. This in effect turns
operator(int a + int b) -> int c
    return __ADD__(a, b)
int i = 3+3

into
int i = __ADD__(3, 3)

This behaviour however can be detrimental and bug prone if the input variable and output variables point to the same location in memory. To use 'safer' behaviour, the unsafe keyword adjusts the compilation process such that additional variables are created and copied to and from the inline as needed.
Scratch variables and complex operations
Mathematical operations such as a += (b + c) * 4 cannot be calculated without using extra memory cells. The high level compiler deals with this by seperating the operations into different sections:
scratch_1 = b + c
scratch_1 = scratch_1 * 4
a = a + scratch_1

This introduces the concept of scratch variables which are used for storing intermediate information of calculations. They're allocated as required and deallocated into the general pool once finished with. This decreases the number of scratch memory locations required for use. Scratch variables are considered globals.
Each subroutine has its own VariableStore to keep a reference to all of the variables the subroutine uses as well as their type. At the end of the compilation, they're translated into relative offsets from the start of the store and then given actual addresses in RAM.
RAM Structure
Program counter
Subroutine locals
Operator locals (reused throughout)
Scratch variables
Result variable
Stack pointer
Stack
...

Low level compilation
The only things the low level compiler has to deal with are sub, call_sub, return, assign, if and while. This is a much reduced list of tasks that can be translated into QFTASM instructions more easily.
sub
This locates the start and end of a named subroutine. The low level compiler adds labels and in the case of the main subroutine, adds an exit instruction (jump to end of ROM).
if and while
Both the while and if low level interpreters are pretty simple: they get pointers to their conditions and jump depending on them. while loops are slightly different in that they're compiled as
...
condition
jump to check
code
condition
if condtion: jump to code
...

call_sub and return
Unlike most architectures, the computer we're compiling for doesn't have hardware support for pushing and popping from a stack. This means that both pushing and popping from the stack take two instructions. In the case of popping, we decrement the stack pointer and copy the value to an address. In the case of pushing, we copy a value from an address to the address at the current stack pointer and then incrementing.
All the locals for a subroutine are stored at a fixed location in RAM determined at compile time. To make recursion work, all the locals for a function are placed onto the stack at the start of a call. Then the arguments to the subroutine are copied to their position in the local store. The value of the return address is put onto the stack and the subroutine executes.
When a return statement is encountered, the top of the stack is popped off and the program counter is set to that value. The values for the locals of the calling subroutine are the popped off the stack and into their previous position.
assign
Variable assignments are the easiest things to compile: they take a variable and a value and compile into the single line: MLZ -1 VALUE VARIABLE
Assigning jump targets
Finally, the compiler works out the jump targets for labels attached to instructions. The absolute position of labels is determined and then references to those labels are replaced with those values. Labels themselves are removed from the code and finally instruction numbers are added to the compiled code.
Example step by step compilation
Now that we've gone through all the stages, let's go through an actual compilation process for an actual program, step by step.
#include stdint

sub main
    int a = 8
    int b = 12
    int c = a * b

Ok, simple enough. It should be obvious that at the end of the program, a = 8, b = 12, c = 96. Firstly, lets include the relevant parts of stdint.txt:
operator (int a + int b) -> int
    return __ADD__(a, b)

operator (int a - int b) -> int
    return __SUB__(a, b)

operator (int a < int b) -> bool
    bool rtn = 0
    rtn = __MLZ__(a-b, 1)
    return rtn

unsafe operator (int a * int b) -> int
    int rtn = 0
    for (int i = 0; i < b; i+=1)
        rtn += a
    return rtn

sub main
    int a = 8
    int b = 12
    int c = a * b

Ok, slightly more complicated. Let's move onto the tokeniser and see what comes out. At this stage, we'll only have a linear flow of tokens without any form of structure
NAME NAME operator
LPAR OP (
NAME NAME int
NAME NAME a
PLUS OP +
NAME NAME int
NAME NAME b
RPAR OP )
OP OP ->
NAME NAME int
NEWLINE NEWLINE
INDENT INDENT
NAME NAME return
NAME NAME __ADD__
LPAR OP (
NAME NAME a
COMMA OP ,
NAME NAME b
RPAR OP )
...

Now all the tokens get put through the grammar parser and outputs a tree with the names of each of the sections. This shows the high level structure as read by the code.
GrammarTree file
 'stmts': [GrammarTree stmts_0
  '_block_name': 'inline'
  'inline': GrammarTree inline
   '_block_name': 'two_op'
   'type_var': GrammarTree type_var
    '_block_name': 'type'
    'type': 'int'
    'name': 'a'
    '_global': False

   'operator': GrammarTree operator
    '_block_name': '+'

   'type_var_2': GrammarTree type_var
    '_block_name': 'type'
    'type': 'int'
    'name': 'b'
    '_global': False
   'rtn_type': 'int'
   'stmts': GrammarTree stmts
    ...

This grammar tree sets up information to be parsed by the high level compiler. It includes information such as structure types and attributes of a variable. The grammar tree then takes this information and assigns the variables that are needed for the subroutines. The tree also inserts all the inlines.
('sub', 'start', 'main')
('assign', int main_a, 8)
('assign', int main_b, 12)
('assign', int op(*:rtn), 0)
('assign', int op(*:i), 0)
('assign', global bool scratch_2, 0)
('call_sub', '__SUB__', [int op(*:i), int main_b], global int scratch_3)
('call_sub', '__MLZ__', [global int scratch_3, 1], global bool scratch_2)
('while', 'start', 1, 'for')
('call_sub', '__ADD__', [int op(*:rtn), int main_a], int op(*:rtn))
('call_sub', '__ADD__', [int op(*:i), 1], int op(*:i))
('assign', global bool scratch_2, 0)
('call_sub', '__SUB__', [int op(*:i), int main_b], global int scratch_3)
('call_sub', '__MLZ__', [global int scratch_3, 1], global bool scratch_2)
('while', 'end', 1, global bool scratch_2)
('assign', int main_c, int op(*:rtn))
('sub', 'end', 'main')

Next, the low level compiler has to convert this high level representation into QFTASM code. Variables are assigned locations in RAM like so:
int program_counter
int op(*:i)
int main_a
int op(*:rtn)
int main_c
int main_b
global int scratch_1
global bool scratch_2
global int scratch_3
global int scratch_4
global int <result>
global int <stack>

The simple instructions are then compiled. Finally, instruction numbers are added, resulting in executable QFTASM code.
0. MLZ 0 0 0;
1. MLZ -1 12 11;
2. MLZ -1 8 2;
3. MLZ -1 12 5;
4. MLZ -1 0 3;
5. MLZ -1 0 1;
6. MLZ -1 0 7;
7. SUB A1 A5 8;
8. MLZ A8 1 7;
9. MLZ -1 15 0;
10. MLZ 0 0 0;
11. ADD A3 A2 3;
12. ADD A1 1 1;
13. MLZ -1 0 7;
14. SUB A1 A5 8;
15. MLZ A8 1 7;
16. MNZ A7 10 0;
17. MLZ 0 0 0;
18. MLZ -1 A3 4;
19. MLZ -1 -2 0;
20. MLZ 0 0 0;

The Syntax
Now that we've got the bare language, we've got to actually write a small program in it. We're using indentation like Python does, splitting logical blocks and control flow. This means whitespace is important for our programs. Every full program has a main subroutine that acts just like the main() function in C-like languages. The function is run at the start of the program.
Variables and types
When variables are defined the first time, they need to have a type associated with them. The currently defined types are int and bool with the syntax for arrays defined but not the compiler.
Libraries and operators
A library called stdint.txt is available which defines the basic operators. If this isn't included, even simple operators won't be defined. We can use this library with #include stdint. stdint defines operators such as +, >> and even * and %, neither of which are direct QFTASM opcodes.
The language also allows QFTASM opcodes to be direct called with __OPCODENAME__.
Addition in stdint is defined as
operator (int a + int b) -> int
    return __ADD__(a, b)

Which defines what the + operator does when given two ints.
Comment: @eaglgenes101 For starters, I don't think most of us were aware of the existence of other usable universal computers. The idea for a wireworld-like CA with multiple mixed rules came about as a result of playing around with metacells (I believe - Phi was the one who came up with the idea). From there, it was a logical progression to what we created.
Comment: Can I ask, why was it decided to create a wireworld-like CA in Conway's game of life and create a new processor using this circuitry rather than reuse/retrofit an existing cgol universal computer such [this one](http://conwaylife.com/wiki/Spartan_universal_computer-constructor)?


How can a 3rd Cousin be a DNA match to my mother AND my father's side?

Question: On Ancestry I have a match at the 3rd cousin level and we have common matches with both my mother and fathers side. New to this and that is confusing to me. Sorry if I am missing something obvious!
Comment: There doesn't need to be any endogamy or cousin marriages involved; a simple case of double cousins will do it (siblings from one family marrying siblings from another family). It does mean that the common ancestor(s) are likely to be further back than the 3rd cousin level would otherwise suggest.
Comment: Do you come from an endogamous population -- a population in the past that involved close cousin marriages? Ancestors of your parents might have married.  Ashkenazi Jew are one example, but there are other ancestries with similar characteristics.
Answer: This may simply mean that you and your match are simultaneously related in two different ways.  Just as one example of this, you two could be related in these two ways:

As third cousins through your father's side - one set of your paternal great-great-grandparents are also a (paternal or maternal) set of great-great-grandparents of your match, and
As fourth cousins through your mother's side - one set of your maternal great-great-great-grandparents are also a (paternal or maternal) set of great-great-great-grandparents of your match.

This is just one of many similar variations of possible relationships that you and your match could share.  Figuring out just which possibility is the right one would require that you and your match have or are able to obtain traditional genealogical information about your respective ancestors back to the generations in which you are related.
Answer: Agree with the first two answers entirely but it is also worth remembering that DNA segment transmission is random. It also does not say exactly so much of this chromosome goes here and so much there. It could be a large piece of one chromosome and that stays intact giving a false DNA reading?  I have a number of same surname marriages as evidence of natural returns of DNA? I am not sure this would give third cousin readings but it would not be straight reading of the result. Just some thoughts?

How can a 3rd Cousin be a DNA match to my mother AND my father’s side?


Connecting to a web site with fiddler throws error " SEC_E_ALGORITHM_MISMATCH"

Question: I'm trying to connect to two different RSS feeds at different addresses on the same server (domain names are slightly different) via Fiddler. One site works properly and returns data as expected. The second site returns a 502 error telling me

The client and server cannot communicate, because they do not possess a common algorithm HTTPS handshake returned error SEC_E_ALGORITHM_MISMATCH

The same problem occurs when I use my code to get at the RSS feeds.
If I go to the non-working site with a web browser it works just fine.
I have Fiddler configured to use tls 1.1 & 1.2
In my code I use
<code> ServicePointManager.Expect100Continue = true;
 ServicePointManager.SecurityProtocol = ServicePointManager.SecurityProtocol = SecurityProtocolType.Tls12 | SecurityProtocolType.Tls11;
 var reader = XmlReader.Create(url); <Fails here
 feed = SyndicationFeed.Load(reader);
</code>
Any suggestions for troubleshooting this?
Comment: You can use Wireshark to observe the TLS handshake with both endpoints to identify any differences.
Comment: did you try the solution provided here : https://stackoverflow.com/questions/17595290/fiddler-https-error-because-they-do-not-possess-a-common-algorithm
Comment: What is the point of this? `ServicePointManager.SecurityProtocol = ServicePointManager.SecurityProtocol = ...` Setting something equal to itself is never useful.
Comment: @itsme86  Typo when I cut and pasted my code from VS to here.
Comment: @HazarathChillara Yes tried it. Currently I have Fiddler set to accept SSL3, TLS1.1 & TLS1.2
Answer: Turns out that the government site I am accessing only supports TLS1.0 and our firewall rules don't allow that protocol through.
Our solution may be to change those rules.


How to dynamically increase the length of the url?

Question: How to dynamically increase the length of the url ?
Let me be more descriptive. I want to use it in asp.net version 2.0 and 3.5. The maximum length of the url in (IE 7 +) is 2048.
Various size support in different browsers:
IE 7 + - 2048
Firefox - 65000
Safari - 80000
Opera - 190000
Comment: Why do you want such a long URL?
Answer: Put a query string on the url, and increase the size of it's value:
<code>Response.Redirect("ThisPage.aspx?param=" + Request.QueryString("param") + "x");
</code>
Answer: You add more characters to it.
Answer: Use http://www.hugeurl.com/ ?
Seriously though, nothing stopping you from adding random junk to the query string.  If you want the URL to be immutable, include a checksum or something and require it to match the added text for the URL to resolve.  Or just use a reversible transformation to generate your URL, which is probably what hugeurl does.


Magnetic field units in cgs and SI system

Question: In cgs unit system, the radius of gyration of a particle is:
$$r=\frac{pc}{ZeB}$$
where $p$ is momentum, $c$ is the speed of light $Ze$ is the charge and $B$ the magnetic field.
I'm confused about the units of measure. Let's suppose $B=1G$ (where $G$ is Gauss, the unit for magnetic field in cgs system and $G=10^{-4}T$). And suppose the particle under consideration is a $1GeV$ electron, so that approximately $\frac{pc}{Ze}=10^9V$ (volts). It seems that however the units are in some way wrong, since $V/G$ is not a unit for length. How can I compute the radius correctly?
Answer: You should look at, for example, the appendix of J.D. Jackson, Classical
Electrodynamics where the conversion rules are given.
Your problem is that you are mixing in volts which are not a cgs unit, since Gaussian units do not have an independent extra unit of charge.
In your expression, $pc$ has units of ergs, i.e. $\rm g\cdot cm^2/s^2$.  For 1 Gev
this is about $1.6\times 10^{-3}$ ergs.  $e$ has units of $\sqrt{\rm erg\cdot cm}$
and a value of about $4.8\times 10^{-10}$, ($\frac{e^2}{r}$ is an energy and the conversion factor for charge from Coulombs to cgs is
$2.99792458\times 10^9$ and related to the numerical value of the speed
of light.) Since $B^2$ has units of energy density, $B$ has units of
$\rm \sqrt{erg/cm^3}$ So for your example
\begin{equation}
r = \frac{1.6\times 10^{-3}\rm erg}
{Z 4.8 \times 10^{-10}\rm \sqrt{erg\cdot cm}\cdot 1 \sqrt{erg/cm^3}} =
\frac{1}{3Z} \times 10^{7}\rm cm
\end{equation}
Comment: The charge unit in cgs units is called esu (also statcoulomb or Franklin)
Comment: It is incorrect to suggest $pc$ would represent the kinetic energy of the particle. It may be a good approximation for highly relativistic speeds but otherwise you get completely wrong results with this assumption. See my own answer for details.
Comment: I assumed that  1 GeV meant a momentum of 1 GeV/c, which is a completely standard  way of specifying momentum, and was consistent with the questioner's description with pc= 1 GeV. Of course you are correct if 1 GeV is instead the kinetic energy.
Comment: $1.6x10^{-3}$ ergs is an energy not a momentum. Using it the way you did would lead anybody not familiar with this convention to believe that a particle with e.g. an energy of 10 eV would have a Larmor radius 8 orders of magnitude smaller than for 1 GeV. This would be completely wrong.
Answer: The units are correct in your formula for the Larmor radius. $eB$ has the unit of a force (note that the magnetic field has the same dimension as the electric field in cgs-units). So if you multiply the equation by $eB$ you have on the left side the unit Force x Length = Energy while $pc$ on the right hand side has dimension of energy as well.
However, it is not correct to take $pc$ as the kinetic energy of the particle. This would only be correct for massless particles. In general the relativistic total energy is given by
$$E=\gamma mc^2 = \sqrt{p^2c^2+m^2c^4}$$
and the kinetic energy by
$$K=E- mc^2$$
from which you can see that
$$pc = \sqrt{K^2+2Kmc^2}$$
If you insert $K$ here in cgs-units (erg; 1 eV= $1.6*10^{-12}$ erg) and $e$ and B in cgs units as well (e=$4.8*10^{-10}$ esu; B in Gauss) you will get the correct Larmor radius in $cm$.


Can I log-in to my wallet on new PC using just my wallet number and passphrase?

Question: I was into bitcoin years back. I just stumbled upon my wallet number and passphrase. Can I use these info and sort of log-in using any client I can download online?
Answer: It depends what you mean, but the answer is probably "yes" either way.
Traditional wallets use a wallet.dat file, often encrypted with a password.  In this case, you would need the file and the password in order to use your wallet on a new computer.
Hierarchical deterministic wallets (HD wallets) use a single seed (possibly what you are calling the "wallet number") to regenerate all the addresses in a wallet, thus recreating the wallet.  Often times this seed is stored as word seed (possibly what you are calling the "passphrase"), meaning several randomly generated words that can be fed into an algorithm to regenerate the wallet seed, which in turn regenerates the whole wallet.  If this is what you mean, then you could restore your wallet with either just the seed, or the passphrase.  How to accomplish this from a UI will be determined by the particular wallet you are using.


How to set camera resolution in Android with OpenCV?

Question: I'm trying to develop an app for Android, and I would need to get uncompressed pictures with a resolution as high as possible from the camera. I tried takePicture's rawCallback and postviewCallback, but they are not working.
Right now I'm trying with OpenCV (version 2.4) using VideoCapture, but I'm stuck in the default 960x720, which is poor for what I need; and my phone, a Samsung Galaxy S3, is able to provide, theoretically, up to 8Mpx (3,264×2,448 for pictures, and 1,920×1,080 for video, according to Wikipedia). VideoCapture.set(Highgui.CV_CAP_PROP_FRAME_WIDTH/HEIGHT, some number) makes the camera return a black image as far as I've found.
Is there any way to obtain a higher resolution, either through OpenCV or with the Android API, without compressing?
I'm really sorry if this has been asked before; I have been looking for days and I have found nothing.
Thank you for your time!
EDIT: Although it is not exactly what I was asking, I found that there is a way to do something very similar: if you set an OnPreviewCallback for the Camera, using setPreviewCallback, you do get the raw picture data from the camera (at least in the S3 I'm working with). I leave it here in case somebody finds it useful in the future.
EDIT: A partial solution is explained in an answer below. To sum up,
vc.set(Highgui.CV_CAP_PROP_FRAME_WIDTH, desiredFrameWidth);
vc.set(Highgui.CV_CAP_PROP_FRAME_HEIGHT, desiredFrameHeight);

works under some conditions; please see below for further detail.
Answer: You have to get supported camera preview resoultions by calling getSupportedPreviewSizes.
After this you can set any resolution with method setPreviewSize. And don't forget to setParameters in the end. Actally many OpenCV Android examples contain this information (look at sample3).
Answer: In case anybody ever finds this useful, I found a (partial) solution: If your VideoCapture variable is called vc, this should work:
vc.set(Highgui.CV_CAP_PROP_FRAME_WIDTH, desiredFrameWidth);
vc.set(Highgui.CV_CAP_PROP_FRAME_HEIGHT, desiredFrameHeight);

Mind that the combination of width and height must be one of the supported picture formats for your camera, otherwise it will just get a black image. You can get those through Camera.Parameters.getSupportedPictureSizes().
However, setting a high resolution appears to exceed the YUV conversion buffer's capacity, so I'm still struggling with that. I'm going to make a new separate question for that, to keep everything clearer: new thread
Answer: setPreviewSize does not set picture resolution. setPictureSize does.