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How blocks are chained in a blockchain

Posted on by John

The high-level explanation of a blockchain says that each block contains a cryptographic hash of the previous block. That’s how the blocks are chained together.

That’s not exactly true, and it leaves out a lot of detail. This post will look in full detail at how Bitcoin blocks are chained together by inspecting the bits of two consecutive blocks. Looking at the low-level details reveals that some statements, like the paragraph above, are simplifications and half-truths.

For the purpose of this post, I downloaded two blocks that were added to the blockchain overnight, blocks 920993 and 920994, and saved the blocks in the binary files 920993.dat and 920994.dat.

Hashing headers

According to the simplistic description, the hash of block 920993 should be contained in block 920994. That’s not correct. We will see that the hash of the header of block 920993 is contained in block 920994 [1].

What exactly is the header?

You may hear that the header of a Bitcoin block is the first 80 bytes. That’s also not quite true. The first 4 bytes of a (production) Bitcoin block are the magic number 0xf9beb4d9. This is number chosen by Satoshi with no apparent significance, a random number unlikely to conflict with anything else. Blocks used in test versions of the blockchain begin with different magic numbers.

The next 4 bytes represent the size of the block as an unsigned integer in little endian layout. The magic number and the block size form a sort of pre-header 8 bytes long.

The API that I used to download the blocks does not include the pre-header, so the header is the first 80 bytes of the files I downloaded, though strictly speaking headers are bytes 9 through 89 of the full block.

We can see a hex dump of the header of block 920993 by running

xxd -l 80 920993.dat

which shows us the following.

00e0 ff3f e31d 6937 0e1c dba2 5321 5546
0ecc 00bf 678c a2e1 255e 0100 0000 0000
0000 0000 996f 2b91 fefc dc17 e530 6c70
9672 af27 4361 7608 1ded fde3 1157 10a5
200f 0f83 7022 ff68 21eb 0117 96f2 fbb6

How to hash?

OK, so we’re supposed to hash the header. What hash function should we apply? Bitcoin uses double SHA256,

SHA256²(header) = SHA256( (SHA256(header) )

We can compute this with openssl by running

head -c 80 920993.dat | openssl dgst -sha256 -binary | openssl dgst -sha256

Note that the first invocation of openssl dgst uses the option -binary, instructing the software to pass the raw bytes to the rest of the pipeline rather than display a text representation. The last part of the pipeline does not have that option because we want a human-readable representation at the end. The output is

c2dfb57ef58275c27a6433c5edfddfc1af6ab9ae708c00000000000000000000

Note that there are a lot of zeros on the end of the hash. That’s not a coincidence. More on that later.

Header of the next block

In the previous section we found the hash of block 920993, and we expect to see it inside the header of block 920994.

xxd -l 80 920994.dat

we can see that the header of block 920994 contains the following.

0000 002e c2df b57e f582 75c2 7a64 33c5
edfd dfc1 af6a b9ae 708c 0000 0000 0000
0000 0000 bb15 accc 8940 3811 0b9b e1cf
b125 c0fa a65e fb1b 2fa4 61ed 989f 8d6f
e41e 04cf 5522 ff68 21eb 0117 f2bc ab1a

The first 4 bytes (8 hex characters) are a version number, and following the version number we see the hash we were looking for.

Byte order

Why all the zeros in the hash of the block header? That’s a result of the proof of work problem that had to be solved in order to add block 920993 to the blockchain. Bitcoin miners tweak the details of the block [2] until they create a block whose hash begins with the required number of 0 bits [3].

But the hash value above doesn’t begin with zeros; it ends with zeros. What’s up with that?

The Bitcoin header and openssl dgst both display hashes in little endian order, i.e. the reverse of what you’d expect from a positional number system.

Related posts

[1] But if you only hash the header, couldn’t someone change the rest of the block? No, because the header contains the Merkle tree root. If someone changed a bit in the body of the block, that would change the Merkle tree root, which would change the header, which would change its hash.

[2] They don’t change the substance of the transactions, but they can change the order in which the transactions are included. And there’s a nonce value that they can change too. The only known way to produce a given number of zeros is by trial and error, and so this takes a lot of work. Having a block with the right leading zeros in its hash proves that you’ve put in the work, hence proof of work.

[3] This is another simplified half-truth. You don’t need to produce a certain number of leading zeros per se; you need to find a hash value less than a target value, and the target value is not in general an exact power of 2.

Spacing the circles on the Smith chart

Posted on by John

The previous post looked at the basics of how to create a Smith chart. The Smith chart is the image of a Cartesian grid in the right half-plane under the function

f(z) = (z − 1)/(z + 1).

At the end of the post I noted that evenly distributed grid lines in the z plane result in very unevenly spaced circles on the Smith chart in the w plane. We can fill in the Smith chart how we please by working backward, starting from a desired spacing of circles in the chart and tracing them back to the z plane.

The inverse of the function f is

g(w) = (1 + w)/(1 − w).

Complete circles

The Smith chart contains two kinds of circles: circles that fit entirely inside the chart, which are the images of vertical lines in the z plane, and circles that extend outside the chart, which are the images of horizontal lines. In the image below, the former are blue and the latter are orange.

We can space out the complete (blue) circles how we wish and use the inverse transformation g(w) to determine the corresponding spacing of the vertical lines in the z plane. If we take a point w0 along the horizontal diameter of the Smith chart, w0 is a real number, and so is its inverse z0 = g(w0).

So if we’d like the intersections of the complete circles with the diameter to be uniformly spaced, we pick uniformly spaced points wi and use as our vertical lines in the z plane the lines with real part g(wi).

Here’s the image we’d get if we wanted circles passing through the diameter of the Smith chart at increments of 0.1.

And here’s the corresponding set of vertical lines in the z plane that would produce these circles.

Incomplete circles

Now onto the incomplete circles, the orange circles in the graph above that are perpendicular to the blue circles.

As we showed in the previous post, the outer rim of the Smith chart is the image of the imaginary axis in the z plane under the function f(z). So if we pick a point wi on the rim that we’d like a circle to pass through, we use the horizontal line with imaginary part equal to g(wi).

So if we wanted orange circles to cross the boundary of the Smith chart every 10°, we pick w‘s from the interval [−π, π] spaced π/18 apart.

We can create these lines on the Smith chart below

from these lines in the z plane.

Putting it all together

The image of this grid in the z plane

is the following in the w plane.

Compromise

The Smith charts printed in textbooks use some compromise between even spacing in the w plane and even spacing in the z plane.

Smith chart

Zcash price doubled

Posted on by John

My interest in cryptocurrency is primarily technical, and privacy coins are the most technically interesting. The math behind coins like Monero and Zcash is far more sophisticated than the math behind Bitcoin.

I’m also interested in the privacy angle since I work in data privacy. The zero-knowledge proof (ZKP) technology developed for and tested in privacy coins is applicable outside of cryptocurrency.

I don’t follow the price of privacy coins, but I heard about the price of Zcash doubling recently.

I’d like to understand why that happened, especially why it happened so suddenly, though I’m very skeptical of post hoc explanations of price changes. I roll my eyes when I hear reporters say the stock market moved up or down by some percent because of this or that event. Any explanation for the aggregate behavior of a complex system that fits into sound byte is unlikely to contain more than a kernel of truth.

Update: The price has gone up another 65% in the two days since I wrote this post.

Naval Ravikant said on October 1

Bitcoin is insurance against fiat.
ZCash is insurance against Bitcoin.

This was after Zcash had started rising, so Naval’s statement wasn’t the cause of the rise. But the idea behind his statement was in the air before he crystalized it. Maybe the recent increase in the price of Bitcoin led to the rise of Zcash as a hedge against Bitcoin falling. It’s impossible to know. Traders don’t fill out questionnaires explaining their motivations.

It has been suggested that more people are interested in using Zcash as a privacy-preserving currency, not just buying it for financial speculation. It’s plausible that this could be a contributing factor in the rise of Zcash, though interest in financial privacy is unlikely to spike over the course of one week, barring something dramatic like FDR’s confiscation of private gold in 1933.

The price of Monero increased along with Zcash, though not as by nearly as much.

This suggests there may be increased interest in privacy coins more generally and not just in Zcash.

It would be interesting to see how people are using Zcash and Monero—how much is being spent on goods and services and how much is just being traded as an investment—but this would be difficult since privacy coins obscure the details of transactions by design.

Related posts

Memorizing a list of seed words

Posted on by John

If you need to memorize a list of up to eight words, particularly for a short period of time, the most efficient method may be brute force: rehearse the words in sequence until you can remember them. But if you need to remember more words, or remember the list for a longer time, some sort of peg system would be better.

Pegs

A peg system begins with a list of images firmly associated with integers. You drill these associations into your brain like driving pegs into wood, then “hang” things on the pegs.

The choice of pegs could be arbitrary, but it’s easier to acquire a set of pegs if there’s some pattern to them, such as the Major system. An example set of pegs based on the Major system follows.

  1. tea
  2. Noah
  3. ammo
  4. arrow
  5. law
  6. show
  7. key
  8. ivy
  9. pie
  10. toes
  11. toad
  12. dune

and so on.

Learning a set of pegs is harder than hanging things on the pegs. But once you have a peg system, you can reuse it for many different things.

Numbered lists

Here’s something I resisted but eventually came to accept: it’s easier to memorize a numbered list than an unnumbered list. For example, it’s easier to learned a numbered list of the US presidents—#1 Washington, … #16 Lincoln, … etc.—than to simply learn to recite the list.

This is counterintuitive because it requires memorizing more information. But the key is this: with a numbered list, you only have to remember pairs of pegs and items. To memorize a list of 100 items, you don’t have to memorize a sequence of 100 things; you have to remember a set of 100 pairs. If you forget an item, you forget one item: it doesn’t throw off anything else. It’s also easier to review and test yourself on a numbered list.

I’ve noticed when journalists are reporting on some memory stunt, they’ll say something like “Not only can he recite the Fortune 500, he could pull up each one by number.” Reading between the lines, this person used a peg system. He memorized each company with its number, not to make things harder, but to make things easier.

Seed phrases

A seed phrase for a crypto wallet is a list of 12 to 24 words. You could memorize a list of 12 words by rote without too much effort, but a list of 24 would be more than twice as hard. Since you want to remember wallet seed words for a long time, and there are potentially huge consequences to forgetting part of the list, I’d recommend a peg system.

To create an example, I chose 12 words by sampling the BIP39 word list with replacement using the command

    shuf -n 12 -r english.txt

This returned the following words:

  1. entry
  2. lava
  3. foot
  4. vibrant
  5. diet
  6. pulp
  7. canal
  8. name
  9. noble
  10. dream
  11. breeze
  12. bar

This probably isn’t a valid wallet address, but it’s like one [1].

To memorize the list using the pegs above, you would create mental images associating tea with entry, Noah with lava, ammo with foot, etc. You might imagine Noah’s ark on a sea of lava, or shooting yourself in the foot.

Noah's ark floating on lava

As I’ve written before, some of the BIP39 seed words are less than ideal for memorization. Lava creates a vivid mental image; entry does not. Maybe you could change entry to entryway, imagining a giant teapot in the entryway to your house.

The BIP39 words are uniquely determined by their first four letters. You could change the words if you like, as long as you keep the initial letters the same. For example, if you tried to type entryway into a wallet, autocomplete would kick in after you typed entr and so the rest of the letters don’t matter.

Recall

To recall the list, you go down your list of pegs and see what is associated with each. This is why pegs have to be unique. If you want to encode a number using the Major system, you can encode the same digits different ways at different times. For instance, maybe you encode 12 as Dune one time and Athena the next. But when recalling a list, you need to recall the peg for a number and recall what it’s associated with.

Related posts

[1] The seed words come from a list of 2048 words, so each word carries 11 bits, so 12 words encode a 128-bit address with 4 checksum bits left over. So there’s a 15/16 probability that a list of 12 words does not encode a valid address.

Inverting series that are flat at zero

Posted on by John

The previous post looked at solving the equation

2\theta + \sin(2\theta) = \pi \sin( \psi)

which arises from the Mollweide map projection. Newton’s method works well unless φ is near π/2. Using a modified version of Newton’s method makes the convergence faster when φ = π/2, which is kinda useless because we know the solution is $theta; = π/2 there. When φ is near π/2, the modified Newton’s method may diverge. I ended the previous post by saying a series solution would work better when φ is sufficiently close to π/2. This post will flesh that out.

Let x = π − 2θ. Now the task is to solve

x - \sin(x) = y

for small positive values of y.

The left side is

\frac{x^3}{3!} - \frac{x^5}{5!} + \frac{x^7}{7!} + \cdots

and so for very small values of y, and thus very small values of x, we have

x = (6y)^{1/3}

If this solution is not sufficiently accurate, we can invert the power series above to get a power series in y that gives the solution x. However, the Lagrange inversion theorem does not apply because the series has a zero derivative at 0. Instead, we have to use Puiseux series inversion, looking for a series in y1/3 rather than a series in y. From the Puiseux series we can see that

x = (6y)^{1/3} + y/10

is a more accurate solution. For even more accuracy, you can compute more terms of the Puiseux series.

Morse code beyond the solar system

Posted on by John

Voyager's golden record

The two Voyager probes, launched in 1977, are now in interstellar space beyond our solar system. Each carries a Golden Record, a recording of sounds and encoded images meant to represent Earth and human civilization.

I’ve long intended to listen to the record and yesterday I did. One of the cuts is a 12-minute collage of sounds from our planet. It starts with natural sounds—thunder, crickets, frogs, birds, etc.—and progresses human sounds—a heartbeat, speech, tool use, etc. The sounds appear in roughly historical order, with the sound of a rocket launch toward the end.

At 7:49 there is Morse code on top of other sounds. I was curious what the message was, so I transcribed it: it’s “ad astra per aspera” played twice. This is Latin for “To the stars through hardships.”

Mandelbrot and Fat Tails

Posted on by John

The Mandelbrot set is the set of complex numbers c such that iterations of

f(z) = z² + c

remain bounded. But how do you know an iteration will remain bounded? You know when it becomes unbounded—if |z| > 2 then the point isn’t coming back—but how do you know whether an iteration will never become unbounded? You don’t.

So in practice, software to draw Mandelbrot sets will iterate some maximum number of times, say 5000 times, and count a point as part of the set if it hasn’t diverged yet. And for the purposes of creating pretty graphics, that’s good enough. If you want to compute the area of the Mandelbrot set, that’s not good enough.

A reasonable thing to do is to look at the distribution of escape times. Then maybe you can say that if an iteration hasn’t escaped after N steps, there’s a probability less than ε that it will escape in the future, and make ε small enough to satisfy the accuracy of your calculation.

The distribution of escape times drops off really quickly at first, as demonstrated here. Unfortunately, after this initial rapid drop off, it settles into a slow decline typical of a fat-tailed distribution. This is not atypical: a fat-tailed distribution might initially drop off faster than a thin-tailed distribution, such as the comparison between a Cauchy and a normal distribution.

The plot above groups escape times into buckets of 1,000. It starts after the initial rapid decline and shows the fat-tailed region. This was based on 100,000,000 randomly generated values of c.

To estimate the probability of an iteration escaping after having remained bounded for N steps, you need to know the probability mass in the entire tail. So, dear reader, what is the sum of the areas in the bars not shown above and not calculated? It’s not like a normal-ish distribution when you can say with reasonable confidence that the mass after a certain point is negligible.

This matters because the maximum number of iterations is in the inner loop of any program to plot the Mandelbrot set or estimate its area. If 5,000 isn’t enough, then use 50,000 as the maximum, making the program run 10x longer. But what if 50,000 isn’t enough? OK, make it 100,000, doubling the runtime again, but is that enough?

Maybe there has been work on fitting a distribution to escape times, which would allow you to estimate the amount of probability mass in the tail. But I’m just naively hacking away at this for fun, not aware of literature in the area. I’ve looked for relevant papers, but haven’t found anything.

Vanity addresses

Posted on by John

Bitcoin addresses are essentially hash values of public keys encoded in Base58. More details here.

The addresses are essentially random characters chosen from the Base58 alphabet: uppercase and lowercase Latin letters and digits, with 0 (zero), I (capital I), O (capital O), and l (lowercase l) removed to prevent errors.

You could create an address that begins with chosen characters by generating private/public key pairs and hashing the latter until you get the initial string you want [1]. People have done this. The vanitygen software gives the example of searching for an address that starts with “Love” (after the mandatory initial 1).

$ ./vanitygen 1Love
...                         
Pattern: 1Love
Address: 1LoveRg5t2NCDLUZh6Q8ixv74M5YGVxXaN
Privkey: 5JLUmjZiirgziDmWmNprPsNx8DYwfecUNk1FQXmDPaoKB36fX1o

Search time

You can’t specify a long prefix. The difficulty in finding an address with n specified initial characters grows exponentially, like 58n.

Say it takes a minute on average to find an address with the desired first four characters. Each additional character makes the search take 58 times longer, so specifying 5 characters would take about an hour. If you wanted to find an address that begins 1AcmeCorp it would take 584 minutes or over 21 years.

Disadvantages

There are several reasons you might not want to use a vanity address.

First, it’s now customary to generate new addresses for each transaction. This gives Bitcoin some degree of privacy, though not much. Presumably if you go to the effort of creating a custom address you’d like to hold on to it. Maybe you’d like to use it as an address for someone to send you donations, for example, and you’re OK reusing the address.

Second, if you use software someone else wrote to generate the custom address, the site may hold onto your private key or send it somewhere.

Third, you can’t use the address with an HD wallet. Related to the first point, HD wallets generate a sequence of key pairs, and thus addresses, according to some deterministic algorithm, and so it can’t hold an address it didn’t generate. But there are wallets that will hold such addresses.

Proof of work

Incidentally, the proof-of-work task for Bitcoin is very similar to finding vanity addresses. You take a block and twiddle what you can until it hashes to a value with a target number of leading zero bits. More on that here.

El Salvador’s Bitcoin and Quantum Computing

Posted on by John

The treasury of El Salvador owns over 6,000 Bitcoins. Its total holdings are currently worth roughly $700,000,000. These coins had been associated with one private key. Yesterday El Salvador announced that it would split its funds into 14 wallets in order to protect the funds from quantum computing. You can confirm using a blockchain explorer that this has indeed happened.

The most oversimplified takes say El Salvador has protected its Bitcoin reserves from a quantum computing attack by moving from one wallet to 14 wallets. But moving money from one private key to 14 private keys does not it itself offer any protection against quantum computing. It only means that stealing the funds would take 14 times longer. Unsurprisingly the original announcement is more nuanced than the online commentary on the announcement.

For reasons explained in the previous post, Bitcoins are safe from quantum attack until they are spent. You don’t need to reveal your public key to receive Bitcoins, only a hash of your public key. But you do need to reveal your public key to spend Bitcoins.

As far as I know, the one key that until recently held all of El Salvador’s Bitcoin reserves had never spent coins, and so the public key was never made public. If so, the reserves were already safe from quantum computing attacks, at least to the extent that the reserves are safe now. So, strictly speaking, yesterday’s move did not increase the security of the reserves from quantum attack.

What yesterday’s move accomplished was making it easier to spend part of the reserves. Now one of the wallets could spend reserves, revealing the public key associated with part of the reserves rather than a single key associated with all the reserves.

Splitting one large wallet into multiple smaller wallets is a good move, for reasons that have nothing to do with quantum computing. But there is a quantum angle here, namely that the split reduces the risk of quantum computing attack when some of the funds are spent.

There are proposals to harden the Bitcoin protocol against quantum attacks, and perhaps El Salvador can avoid spending from some or all of its wallets until one of these proposals is implemented.

Related posts

Storing data in images

Posted on by John

This post will connect a couple posts from yesterday and explore storing data in images.

Connections

There’s a connection between two blog posts that I wrote yesterday that I only realized today.

The first post was about the probability of sending money to a wrong Bitcoin address by mistyping. Checksums make it extremely unlikely that a typo would result in an invalid address. And if somehow you got past the checksum, you would very likely send money to an unused address rather than an unintended used address.

The second post was about QR codes that embed images. I give a couple examples in the post. The first is a QR code that looks like the symbol for a chess king that links to my Kingwood Data Privacy site. The second is a QR code that looks like the icon for @CompSciFact and links to that account’s page on X.

Someone responded to the first post saying that nobody types in Bitcoin addresses; they scan QR codes. The second post suggests QR codes are very robust. I wrote the post just having fun with the novelty of using QR codes in an unintended way, but there is a pragmatic point as well. The fact that you can play with the pixel sizes enough to create images means that there is a lot of safety margin in QR codes.

If you send Bitcoin by scanning a QR code, it’s very likely that you will scan the code correctly. The individual pixels are robust, and QR codes have checksums built in. If somehow you managed to incorrectly scan a QR code for an address, bypassing QR code checksums, then the protections mentioned in the typo post come into play. The checksums in a Bitcoin address apply whether mistype or mis-scan an address.

Storing data on paper

QR codes are a way to store a relatively small amount of data in an image. How much data could you store in an image the size of a sheet of paper?

Ondřej Čertík did an experiment to find out. He wanted to see how much data he could store on a piece of paper using a regular printer and reliably retrieve the data using a phone camera. You can find his results here.

QR code internals

I’ve thought about blogging about how the error detection and correction in QR codes works, but it’s too complicated. I like writing fairly short articles, and QR error correction is too complicated to describe in say 300 words. Other people have written long articles on how it works, and you can find these articles if you’re interested.

It might be possible to write a short article about why it takes a long article to describe QR code error correction. That is, it might be possible to describe briefly the reasons why the algorithm is so complicated. I imagine part of the complexity is just historical contingency, but I also imagine the problem has some intrinsic complexity that isn’t obvious at first glance.

Ondřej used Golay codes for error correction, and it worked fairly well. It would be interesting to compare the robustness of QR codes to a design that simply used Golay codes.

From Bitcoin to Jupiter

James Burke hosted a BBC series called Connections in which he would trace unexpected lines of connections. For example, I recall watching one episode in which he traced the connection between a touchstone and nuclear weapons.

In this post we’ve connected Jupiter to Bitcoin. How? Bitcoin addresses lead to a discussion of QR codes, which lead to discussing Ondřej’s experiment, which led to Golay codes, which were used on a Voyager probe to Jupiter.