random number generator

30 Articles

Roll The Radioactive Dice For Truly Random D&D Play

November 2, 2022 by 22 Comments

When you have a bunch of people gathered around a table for a “Dungeons & Dragons” session, you have to expect that things are not always going to go smoothly. After all, people who willingly create and immerse themselves in an alternate reality where one bad roll of the dice can lead to the virtual death of a character they’ve spent months or years with can be traumatic. And with that trauma comes the search for the guilty — it’s the dice! It’s always the dice!

Eliminating that excuse, or at least making it statistically implausible, is the idea behind this radioactively random dice roller. It comes to us from [Science Shack] and uses radioactive decay to generate truly random numbers, as opposed to the pseudorandom number generators baked into most microcontrollers. The design is based on [AlphaPhoenix]’s muon-powered RNG, but with a significant twist: rather than depending on background radiation, [Science Shack] brought the power of uranium to the party.

They obtained a sample of autunite, a weird-looking phosphate mineral that contains a decent amount of uranium, perfect for stimulating the Geiger counter built into the dice roller. Autunite also has the advantage of looking very cool under UV light, taking on a ghostly “fuel rod glow,” in the [Homer Simpson] sense. The decay-powered RNG at the heart of this build is used to simulate throws of every standard D&D die, from a D4 to a D100. The laser-cut hardboard case holds all the controls and displays, and also has some strategically placed openings to gaze upon its glowing guts.

We really like the design, but we have to quibble with the handling of the uranium ore; true, the specific activity of autunite is probably pretty low, but it seems like at least some gloves would have been in order.

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Yes We Have Random Bananas

June 12, 2022 by 36 Comments

If you ask a normal person to pick a random number, they’ll usually just blurt out a number. But if you ask a math-savvy person for a random number, you’ll probably get a lecture about how hard it is to pick a truly random number. But if you ask [Valerio Nappi], you might just get a banana.

His post, which is in two parts, details how what computers generate are actually pseudo-random numbers. You can easily make sure that every number has the same probability of selection as any other number. The problem is that you have to start with something — usually called a seed. For the purposes of playing games, for example, you can grab some source of entropy like how many microseconds since a hardware timer last rolled over, the number of input pulses you’ve received from a mouse lately, or how long you had to wait for the enter key to depress after asking the user to press it. But if you know that seed and the algorithm you can perfectly predict what number the computer will generate next so it isn’t truly random.

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Dice Rolls From The Beginning Of Time

January 5, 2022 by 30 Comments

Generating random numbers might seem like a trivial task, that is until the numbers need to be truly random for cryptography or security reasons. When that’s the case, it turns out that these numbers are really “pseudo-random” and follow a predictable pattern. Devices that can produce truly random numbers often do it by sampling random events in the real world rather than relying on a computer to do it directly, like this machine which simulates a dice roll by looking at the cosmic microwave background radiation.

The cosmic microwave background radiation exists in the infrared at the farthest edges of the observable universe as a remnant of the big bang. It’s an excellent source of randomness, but tapping into it poses a bit of a challenge. For this build, [iSax] is using an old Soviet-era Geiger tube to detect the appropriate signal, and a Nixie tube to display the dice roll. After the device detects two particles from the Big Bang, the device measures the amount of time that passed between the detection of both particles and uses this number to calculate the dice roll.

While it takes a little bit longer to roll this dice than a traditional one since it has to wait to detect the right kind of particles, if you really need the randomness it can’t be beat. It certainly works as dice, but we can also see some use for generating truly random numbers for other applications as well. For some other sources of random inspiration be sure to check out our own [Voja Antonic]’s deep dive into truly random number generation.

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Random Numbers From A Smoke Detector

June 26, 2021 by 21 Comments

The quest for truly random numbers is something to which scientists and engineers have devoted a lot of time and effort. The trick is to find an unpredictable source of naturally occurring noise that can be sampled, so they have looked towards noisy gas discharge tubes or semiconductor junctions, and radioactive decay. Noisy electrical circuits have appeared in these pages before as random number generators, but we’d be forgiven for thinking that radioactive decay might involve something a little less run-of-the-mill. In fact we all probably have just such a device in our houses, in the form of the ionisation chamber that’s part of most household smoke detectors. [Lukas Koch] has built a project that shows us just how this can be done.

A smoke detector of this type uses a metal shell to house a tiny sample of radioactive americium that emits alpha particles into the space between two electrodes. These ionise the air in that space, and the detectable effect on the space between the two electrodes is increased when ionised gasses from smoke are present. However it can also quite happily detect the ionisation from individual alpha particles, which means that it’s perfect as a source of random noise. A sensitive current amplifier requires significant shielding to avoid the device merely becoming a source of mains hum, and to that end he’s achieved a working breadboard prototype.

This is still a work in progress and though it has as yet no schematic he promises us that it will arrive in due course. It’s a project that’s definitely worth watching, because despite getting more up-close and personal than most of us have with radioactive components, it’s one we’re genuinely interested to see come to fruition.

Of course, we’ve seen smoke detectors in more detail before here at Hackaday.

Bet You Didn’t Know Arduinos Are Psychic

November 24, 2020 by 3 Comments

Are you running out of ways to entertain yourself and your family? If you’ve read all the books and watched all the movies, it might be time to explore the psychic abilities of silicon. [Hari Wiguna] has just the trick to keep them guessing for a good long time.

This trick doesn’t take much, just a couple of Arduinos, some momentary buttons, a number pad, and a large helping of math. As you can see in the demo after the break, there is nothing connecting the two, not even 802.11(n). On the randomizer Arduino, [Hari] generates random numbers with the push of a button until the audience sees one they like. Then [Hari] locks in the number with the other button.

What happens next is key: the randomizer generates another random number, but uses it as a hint to set a sentinel digit. The randomizer Arduino subtracts the larger of the two digits in the number from nine and stores the result as the flag. When the next number comes up that has the flag digit in the correct place, the number after that will be the random number chosen at the beginning.

The psychic Arduino’s secret is that it knows the first guess it receives is special. It does the same sentinel digit math as the randomizer, so when the guesser enters the guess with the sentinel digit, it knows the next number entered is the winner. Clear as mud? Check out the second video below where [Hari] explains the trick, a new take on a magic classic.

Looking for a more exciting way to generate random numbers? Try using fish tanks, lava lamps, or muons from outer space.

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Flipping A Coin 10,000 Times With A Dedicated Machine

July 21, 2020 by 31 Comments

Flipping a coin is often the initial example used to help teach probability and statistics to maths students. Often, there is talk of how, given a fair coin, the probability of landing heads or tails should approach 0.5. Of course, if you want to test this, it pays to have a machine do the hard work for you. [Andrew Consroe] has the rig to do just that.

The build consists largely of 3D printed parts. A large cylindrical shroud is used to keep the coin within the flipping area. A spring-loaded dowel is actuated by a stepper motor spinning a cam, which flips the coin. Once the coin has landed, it is photographed with a webcam. An image processing pipeline then determines whether the coin landed heads or tails. A black spot is used on one side of the coin to aid analysis, as the poor-quality webcam images weren’t good enough to recognise the coin in its standard form. Once the flip has been analysed, a sliding aperture is used to push the coin back towards the flipper for the next cycle.

The machine completes a flip approximately every two seconds, meaning 10,000 flips would take approximately 2.5 days. Unfortunately, due to noise and occasional coin escapes, [Andrew] hasn’t yet been able to achieve his goal. He aims to increase speed significantly before making an all-out attempt.

Coin flips can make for decent random numbers, but if you need better ones, perhaps NIST can help you out. Video after the break.

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Finding The Random Seed Of Minecraft’s Title Screen

July 20, 2020 by 12 Comments

Minecraft is a game about exploring procedure-generated worlds. Each world is generated from a particular “seed” value, and sharing this seed value allows others to generate the same world in their own game. Recently, the distributed computing project Minecraft@Home set about trying to find the seed value of the world shown in the Minecraft title screen, and have succeeded in their goal.

The amount of work required to complete this task should not be underestimated. 137 users contributed 181 hosts with 231 GPUs to the effort, finding a solution in under 24 hours. The list of contributors to the project is a long one. It appears the method to find the seed involved comparing screenshots from various seed worlds to the original image. This took a lot of reverse engineering in order to calculate the camera FOV and other settings of the original capture, such that the results could be compared accurately. Interestingly, the group found two seeds that can generate the requisite world, suggesting the world generator code has some collisions between seed values.

We’re not sure what’s more astounding, the amount of work that went into the project, or that there’s a distributed computing project tackling advanced Minecraft research. Either way, we’re no strangers to Minecraft hacks around these parts. Video after the break. Continue reading “Finding The Random Seed Of Minecraft’s Title Screen” →