Ada and the music machine

by Paul Curzon, Queen Mary University of London

A man playing a barrel organ with a soft toy monkey.
Image by Holger Schué from Pixabay

Charles Babbage found barrel organs so incredibly irritating that he waged a campaign to clear them from the streets, even trying to organise an act of parliament to have them banned. Presumably, it wasn’t the machine Babbage hated but the irritating noise preventing him from concentrating: the buskers in the streets outside his house constantly playing music was the equivalent to listening to next door’s music through the walls. His hatred, however, may have led to Ada Lovelace’s greatest idea.

It seems rather ironic his ire was directed at the barrel organ as they share a crucial component with his idea for a general purpose computer – a program. Anyone (even monkeys) can be organ grinders, and so play the instrument, because they are just the power source, turning the crank to wind the barrel. Babbage’s first calculating machine, the Difference Engine was similarly powered by cranking a handle.

The barrel itself is like a program. Pins sticking out from the barrel encode the series of notes to be played. These push levers up and down, which in turn switch valves on and off, allowing air from bellows into the different pipes that make the sounds. As such it is a binary system of switches with pins and no pins round the barrel giving instructions meaning on or off for the notes. Swap the barrel with one with pins in different positions and you play different music, just as changing the program in a computer changes what it does.

Babbage’s hate of these music machines potentially puts a different twist on Ada Lovelace’s most visionary idea. Babbage saw his machines as ways to do important calculations with great accuracy, such as for working out the navigation tables ships needed to travel the world. Lovelace, by contrast, suggested that they could do much more and specifically that one day they would be able to compose music. The idea is perhaps her most significant, and certainly a prediction that came true.

We can never know, but perhaps the idea arose from her teasing Babbage. She was essentially saying that his great invention would become the greatest ever music machine…the thing he detested more than anything. And it did.


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

I Ching binary

by Paul Curzon, Queen Mary University of London

Bright green bamboo stalks on a brihgt green background
Image by Sushuti from Pixabay

I Ching the ancient Chinese divination text, several thousand years old, is based on a binary pattern…

I Ching is one of the oldest Chinese texts. The earliest copies date from around 3000 years ago. It uses 64 hexagrams: symbols consisting of six rows of lines (see right). Each row is either a solid horizontal line or two shorter lines with a gap in the middle. The 64 hexagrams are all the possible symbols that can be made from six rows of lines in this way. In I Ching, they each represent possible predictions about the future (a bit like horoscopes). To use I Ching, a series of hexagrams were chosen. This was done in some unknown but random way, using stalks of the Yarrow plant, standing in for dice. The chosen hexagrams then told the person something about their future.

In the earliest versions of I Ching, the order of the hexagrams suggests that they were not thought of as numbers as such. However, in a later version, from around 1000 AD the order in which they appear is different. Thought to be written by a Chinese scholar, Shao Y\0x014Dng, it is this version that Leibniz was given and that aroused his interest because the order of the hexagrams follows the pattern we know of as binary (see Predicting the future). Shao Y\0x014Dng had apparently picked the sequence deliberately because of the binary pattern, so understood it as a counting sequence, if not necessarily how to do maths with it.

How do the hexagrams correspond to binary? It is not in the lines themselves but the pattern of line breaks down the middle that matters. Think of a break in the lines as a 0 (yin) and no break as a 1 (yang). The order, as Leibniz realised, is a counting system, equivalent to our decimals but where you only have two digits (0 and 1) rather than our ten digits (0…9).

I Ching Hexagrams for numbers 0 to 7
I Ching Hexagrams for numbers 0 to 7

Whereas in decimal each column of a number like 123 represents a power of 10 (ones, tens, hundreds, …) in binary each column represents a power of 2 (ones, twos, fours, eights, …). To work out the value that the number represents you multiply each digit by its column value and add the results. So in decimal, 123 represents one hundred plus two tens plus three ones (one hundred and twenty three). 1011 in decimal represents one thousand plus no hundreds plus one ten plus a one (one thousand and eleven). In binary, however, 1011 represents instead one eight plus no fours plus one two plus a one (8+0+2+1) so eleven. It is just a different way of writing down numbers.

Investigating the I Ching pattern helped Leibniz to work out the mathematics of binary arithmetic and on to thinking about machines to do calculations using it.


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

Predicting the future: marble runs, binary and the I Ching

by Paul Curzon, Queen Mary University of London

Image by Sergio Camacho Camacho S. A. from Pixabay

Binary is at the core of the digital world, underpinning everything computers do. The mathematics behind binary numbers was worked out by the great German mathematician Gottfried Wilhelm Leibniz in the 17th century. He even imagined a computing machine a century before Babbage, and two centuries before the first actual computers. He was driven in part by an ancient Chinese text used for divination: predicting the future.

I Ching

Leibniz was interested in the ancient Chinese text, the I Ching because he noticed it contained an intriguing mathematical pattern. The pattern was in the set of 64 symbols it used for predicting the future. The pattern corresponded to the counting sequence we now know of as binary numbers (see I Ching binary). Leibniz was obviously intrigued by the patterns as a sequence of numbers. Already an admirer of the great Chinese philosopher, Confucius, he thought that the I Ching showed that Chinese philosophers had long ago thought through the same ideas he was working on. Building on the work of others who had explored non-decimal mathematics, he worked out the maths of how to do calculations with binary: addition, subtraction, multiplication, and division as well as logical operations such as ‘and’, ‘or’ and ‘not’ that underpin modern computers.

Algorithms embedded in machines

Having worked out the mathematics and algorithms for doing arithmetic using binary, he then went further. He imagined how machines might use binary to do calculations. He also created very successful gadgets for doing arithmetic in decimal, but saw the potential of the simplicity of the binary system for machines. He realised that binary numbers could easily be represented physically as patterns of marbles and the absence of marbles. These marbles could flow along channels under the power of gravity round a machine that manipulated them following the maths he had worked out.

His computer would have been a giant marble run!

A container would hold marbles at the top of a machine. Then, by opening holes in its base above different channels, a binary number could be input into the machine. An open hole corresponded to a 1 (so a marble released) and a closed hole corresponded to a 0 (no marble). The marbles rolled down the channels with each channel corresponding to a column in a binary number. The marbles travelled to different parts of the machine where they could be manipulated to do arithmetic. They would only move from one column to another as a result of calculations, such as carry operations.

Addition of digits in binary is fairly simple: 0+0 = 0 (if no marbles arrive then none leave); 0+1 = 1+0 = 1 (if only one marble arrives then one marble leaves; (1+1 = 2 = 10) if two marbles arrive in a channel then none leave that channel, but one is passed to the next channel (a carry operation). The first rules are trivial, open the holes and either a marble will or will not continue. Adding two ones is a little more difficult but Leibniz envisioned a gadget that did this, so that whenever two marbles arrived in a channel together, one was discarded, but the other passed to the adjacent channel. By inputting two binary numbers into the same set of channels connected to a mechanical gadget doing this addition on each channel, the number emerging is a new binary number corresponding to the sum.

Multiplication by two can be done by shifting the tray holding the number along a place to the left. In decimal, to multiply a number by ten, we just put a 0 on the end. This is equivalent to shifting the number to the left: 123 becomes 1230. In binary the same thing happens when we multiply by 2: put a 0 on the end so shift to the left and the binary number is twice as big (11 meaning 2+1 = 3 becomes 110 meaning 4+2+0 = 6). Multiplication of two numbers could therefore be done by a combination of repeated shifts of the marbles of one number, releasing copies of it or not based on the positions of the 1s in the other number. The series of shifted numbers were then just added together. This is just a simplified version of how we do long multiplication.

To multiply 110 by 101, you multiply 110 by each digit of 101 in turn. This just involves shifts, and then discarding or keeping numbers. First multiply 110 by 1 (the ones digit of 101) giving 110. Write it down. Now shift 110 one place to give 1100 and multiply by 0 (the twos digit of 101). This just gives 0000. Write it below the previous number. Shift 110 by another place to give 11000. Multiply it by 1 (the fours digit of 101). That gives 11000. Write it down below the others. Add all three numbers to get the answer (see box).

The basics of a computer

Leibniz had not only worked out binary arithmetic, the basis of a computer’s arithmetic-logical unit (ALU), he had also seen how binary numbers could flow around a machine doing calculations. Our computers use pulses of electricity instead of marbles, but the basic principles he imagined are pretty close to how modern computers work: binary numbers being manipulated as they flow from one computational unit to the next. Leibniz didn’t make his machine, it was more a thought experiment. However, helped by I Ching, a book for divining the future, he did essentially predict how future computers would work.


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

Mary Coombs, teashops and Leo the computer

by Jo Brodie, Queen Mary University of London

Image by Pexels from Pixabay

Tea shops played a surprisingly big role in the history of computing. It was all down to J. Lyons & Co., a forward thinking company that bought one of the first computers to use for things like payroll. Except they had a problem. Computers need programs, but no such programs existed, and neither did the job of programmer. How then to find people to program their new-fangled computer? One person they quickly found, Mary Coombs, suited the job to a T, becoming the first female commercial programmer.

J Lyons and Company, a catering company with a chain of over 200 tea shops in London, wanted to increase its sales and efficiency. With amazing foresight, they realised computers, then being used only for scientific research in a few universities, would help. They bought the technology from Cambridge University, built their own and called it LEO (the Lyons Electronic Office). They hoped it would do calculations much more quickly than the 1950s clerks could, using calculating machines. But it could only happen if Lyons could find people to program it. At the time there were only a handful of people in the world who were ‘good at computers’ (programmer didn’t exist as a job yet) so instead they had to find people who could be good with computers and train them for the job. Lyons created a Computer Appreciation Course which involved a series of lectures and some homework, all designed to find staff within the company who could think logically and would learn how to write programs for LEO.

One of those was Mary Coombs. Born in 1929, she studied at Queen Mary University of London in the late 1940s. You might think, given that this is about a computer, that she studied computer science, but she actually studied French and History. She couldn’t study computer science: what we’d call a computer science course didn’t exist. There wasn’t one anywhere until 1953, when the University of Cambridge opened a Diploma in Computer Science.

By then, Mary was already working at Lyons. She’d had a holiday job there in 1951, as a clerk (in the Ice Cream Sales department) as she finished her degree. A year later she returned to the company where her career changed direction. In addition to her language skills, she was good at maths so transferred to Lyon’s Statistical Office. That’s where she heard about LEO and the need for programmers to learn about it and help test it as it was being built and refined. Intrigued, she signed up for the company’s first computer appreciation course, did well, and was one of only two people on the course then offered a job on the project. As a result she became the first woman to work on the LEO team as a programmer and the first female commercial programmer in the world.

LEO was an enormous computer, built from several thousand valves, and took up an entire room, though it could only store a few kilobytes of memory. It was also a little temperamental. It needed to be very reliable if it was going to be of any use, so it underwent months of testing and improvement, with Mary’s help, before it was put to work on solving real problems, again with Mary and others on the team writing the programs for everything it did.

One of its first tasks was to make sure everyone got paid! LEO was able to calculate forty people’s payslips in one minute (one every 1.5 seconds) where previously it would have taken one clerk six minutes to do one: a huge improvement in efficiency for Lyons.

LEO was both pioneering and a big success, but the real pioneers were the programmers like Mary. They turned computers, intended to help scientists win Nobel prizes, into ones that helped businesses run efficiently, ensuring people got paid. Obvious now, but remarkable in the 1950s.


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

A custard computer

by Paul Curzon, Queen Mary University of London

This simplistic custard contraption is inspired by a more sophisticated custard computer invented by Adrian Johnstone, Royal Holloway, University of London.

Custard dripping downwards
Image by Bruno / Germany from Pixabay

Imagine a room-sized vat of custard suspended from the ceiling. Below are pipes, valves and reservoirs of custard. At the bottom is a vast lake where the custard collects as it splurges out of the pipes. A pump sucks custard back up to the vat on the ceiling once more. Custard flows, sits, splurges…all the while doing computation.

Babbage worked out how to make a computer using wheels. How might you make a general purpose digital computer out of custard? (It sounds more fun!) Adrian Johnstone at Royal Holloway has designed one and if built it would look something like our above description, like something from Willie Wonka’s chocolate factory.

Here we give a slightly simplistic version. The first step is to have something to represent 0 and 1. That’s easy with custard: no custard in a storage tank is a 0 and custard is a 1. Out of that you can represent numbers using collections of such tanks: lots of tanks containing custard or no custard, with a code (binary) giving them meaning as numbers.

Once you have a way to represent numbers, the next step to making a computer is to make the equivalent of transistors. Transistors are just switches, but ones that revolutionised electronics to the point that they have been hailed as one of the greatest inventions ever. Starting with humble transistors, computers (and lots more) can be built.

Transistors have three inputs. One acts as the data input, or source, connected ultimately to the source of the current (in our case the vat of custard). Another, the drain, connects ultimately to the place the current drains to (in our case the lake of custard). A third input is the gate. It switches the transistor on and off, either allowing current (custard) to flow towards the drain or not. The gate thus acts as the switch to allow custard to flow.

One way to make a custard transistor would be to use a contraption based on your toilet but full of custard (don’t think about that too much). Look in your toilet cistern and see how it switches water on and off when you flush the toilet to get the idea. For a (custard) transistor, have a small tank of custard with a ball floating on the surface. It acts as the gate. Fastened to the end of the ball is a lever The lever’s other end can push up against the end of the pipe that runs from source to drain, blocking the flow. When the tank is full of custard it pushes the other end of the lever down, letting custard flow. If the tank empties then the ball drops, so the other end of the lever rises and blocks the flow.

Transistors have been hailed as one of the greatest inventions ever.

There are two kinds of transistors. They differ in that the gate just operates in opposite fashions. With one kind, custard can flow from source to drain only when there is current (custard) at the gate (as above). In the other, custard flows only when there is no custard at the gate.

Transistor circuit symbol

Once you have (custard) transistors, you can make (custard) logic gates (NOT, AND, OR,…). A (custard) NOT, for example, would need to let custard into its out pipe only if there were no custard on its input pipe (and vice versa). We can do this using a transistor with the NOT circuit’s input connected to the gate, and where custard flows only when the gate has no custard. The drain of the transistor becomes the output of the NOT circuit. The source of the transistor connects to the vat of custard to provide the custard that will flow when the transistor switches on. When custard arrives at the gate which is acting as a switch, it stops custard flowing to the drain, and vice versa, as required.

AND logic needs to let custard out only when there is custard at both its input pipes. OR logic allows custard through when there is custard at either of its input pipes. This can be done with appropriate plumbing together of the transistors as follows.

Diagram of a custard transistor
A custard transistor: when there is
custard at the gate, custard flows
from source to drain. When no
custard is at the gate, the floating ball
drops and closes the link.

A (custard) AND uses two transistors It allows custard to flow when there is custard at both gates which are the input pipes of the AND circuit. Connect one input of the AND circuit to the gate of the first transistor with the source connected to the vat of custard. Connect its output to the source of the second transistor. The gate of this second transistor is linked to the second input of the AND. Custard will flow from the vat down towards the drain only when there is custard at both gates. If either gate has no custard, then the custard will not flow, just as required for custard AND logic. We will leave you to work out how to make (custard) OR logic.

Once you can create gadgets that do (custard) NOT, AND and OR, you can then start to build more interesting circuits by combining them: building up the components of a computer like (custard) adders and (custard) multipliers, circuits that compare numbers and ones that trigger custard to be moved about… put it together in the right way and you can build a computer with control unit, arithmetic logic unit, memory unit and so on… (as long as you have enough custard).

Out of the glooping vat of custard, computation emerges….Would it really work? You would have to build it to find out!


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

The taming of the screw

by Paul Curzon, Queen Mary University of London

Image by Alexas_Fotos from Pixabay

Charles Babbage had an obsession for precision and high standards because if his machines were to work, they needed it. One of his indirect contributions to contraption construction the world over concerned the humble screw. We take screws pretty much for granted now, especially the idea that there are standard sizes. Lose one when putting together that flatpack furniture and you can easily get another that is identical. Before the 1800s though that was not the case. Screws made by different people were unlikely to be the same and might only fit the specific thing they were hand made for. Babbage’s demands for precision helped change that.

The key person in the invention of the standard screw was Stockport engineer, Sir Joseph Whitworth. Having worked as a boy in his uncle’s Derbyshire cotton mills, he was fascinated by the machinery there. He realised the accuracy of the workmanship in the machines was poor and needed to be better.

The Difference Engine was built by Joseph Clement in the years up to 1833, and who should be there helping him do so, having moved on to start a career as a skilled mechanic? None other than Whitworth. For Babbage’s machines to work they needed precision engineering of lots and lots of identical parts and to levels of accuracy far greater than previously needed. For the Difference Engine Clement and Whitworth, with their shared passion for accuracy, were up to the challenge. This work showed the coming need for ways to engineer ever more precisely, and to be able to repeat that work…a challenge Whitworth pursued for the rest of his life.

Also famous for inventing the first ever truly accurate “sniper rifle” he went on to create a standard thread for screws that then became the world’s first national screw thread standard: the British Standard Whitworth system. It suddenly meant screws could be made by mass production, bought from anywhere, and guaranteed to fit precisely for whatever job was needed. Whilst sadly the need to mass produce computers didn’t materialise, the standard was adopted for building ships, trains… for industry throughout the nation, making Great Britain’s industry more efficient and so more competitive. Now we rely on the idea of national and international standards like this not just for hardware but for software too. Standards help ensure our computers work but also keep us safe.

The equivalent of this engineering precision is still lacking in the development of software though, much of which is buggy and developed to poor standards by people hacking out software that may or may not work. High standards tend only to apply in safety-critical software, and then often poorly. We need the next generation of programmers to have the same obsession for precision of Babbage and Whitworth and apply it to the development of software, ending the age of buggy, poorly developed software.


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

Quicksilver memory

by Jo Brodie and Paul Curzon, Queen Mary University of London and Adrian Johnstone, Royal Holloway, University of London

Silvery liquid twisting as it flows downwards.
Image by Roman Shashko from Pixabay

Some 1950s computers used tubes filled with mercury as a memory to store numbers. Mercury is a metal that is liquid at room temperature. It’s also known as quicksilver as it flows very easily, but in computing it was actually used to trap information.

Early computers needed a way to store data that would survive indefinitely, even if the computer was stopped. ‘Delay lines’ provided the solution. Data arriving electronically at a mercury delay line struck a converter (called a ‘transducer’) which converted the information to a sound pulse in the mercury. The sound travelled through the tube at the speed of, yes, sound and when the pulse reached the other side it hit another transducer and was returned to its electronic form. That might not sound (sorry) like much of a delay but compared to the speed that an electrical signal moves through a wire (a fraction of the speed of light), it’s like a gentle stroll. Once inside the mercury tube the sound pulses could be looped back and forth, safely ‘parked’ until needed. The computer would use its clock to help it count how many pulses had passed and a microphone listened for the right time to release it from the memory store back into the circuitry to do a calculation with it.

Mercury is expensive, so computer pioneer Alan Turing recommended using gin instead. He claimed its mix of alcohol and water gave perfect properties for the job while being so much cheaper.

Think about tennis serving machines that shoot balls at you. If you put one in a squash court, then a ball being fired will bounce back and forth off the walls but quickly drop to the floor. A delay line works like having two machines facing each other. One fires a ball so that it hits a lever (the transducer) which tells the other machine to fire a ball back, which then hits a lever on the first machine… and so on. Now there is always a ball in flight (a pulse in the delay line) because the motion of the original ball is detected, and used to make a new ball (pulse) that is injected back into the system. Start the first machine by making it fire balls in an initial ball-no-ball pattern and the system stores that pattern, that information. Using cunning contraptions, motion can keep information firmly in one place.


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

Babbage’s triumph over brutal reality

by Adrian Johnstone, Royal Holloway, University of London and Paul Curzon, Queen Mary University of London

A red rose on a gravestone
Image by Goran Horvat from Pixabay

Charles Babbage is famous for his amazing technical skills in designing a computer, but also infamous for his apparent spiky and obsessive personality.

He certainly seems to have had poor social skills in that he often immensely irritated the people who funded his work. Part of the reason he never managed to complete a working version of his computer is that his funders pulled the plug on him. If only he had had better people skills to complement his technical skills and creativity, perhaps we would have had computers a century earlier! However, perhaps we should be less harsh. He wasn’t a total social misfit: his salons (Victorian high society parties) were extremely popular, and attended by what would now be considered celebrity A-listers. They often centred around demonstrations of science and engineering wonders, so presumably he could be the life and soul of the party… as long as he had a technological wonder to talk about. The young Ada Lovelace attended one such salon and was enthralled by his machines. Encouraged by her mathematically trained mother, Lady Byron, she studied maths and in 1840 collaborated with Babbage on a description of his Analytical Engine.

More to the point, if you consider the context of Babbage’s life, he suffered extremes of grief. In one year alone, 1827, he buried three of his children as well as his wife. Of his eight children only three survived beyond the age of ten. That was the brutal reality of the pre-antibiotic world.

In this context perhaps it is better to think about his work and achievements, as a response to adversity. That he achieved so much is a triumph of ambition over terrible loss.


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

Babbage’s Adders

by Paul Curzon, Queen Mary University of London and Adrian Johnstone, Royal Holloway, University of London

Blue smoke curling over a black background

image by Hanjörg Scherzer from Pixabay

Charles Babbage famously designed the first computer: a steam powered contraption that was never built. At its core was something very simple and elegant: a cunning contraption that allowed his machines to store numbers and do arithmetic, all made of Victorian tech: metal wheels and levers.

Babbage’s Analytical Engine, had it been built, would have been the first working general-purpose computer. The size of a factory, and powered by a steam engine, it was the ultimate cunning contraption. A giant whirring, clanking, puffing mechanical brain. Babbage’s first attempt at mechanical computation, though, was a simpler machine, the Difference Engine. It could only do a fixed, if very useful, kind of calculation. It computed what are called polynomials: patterns of additions and multiplications. It used a complicated adding mechanism. Later, whilst working on designs for his ambitious Analytical Engine he thought of a much simpler adder (described below). His second Difference Engine used this new adder and so needed about 16,000 fewer parts! The Science Museum built it in the twentieth century.

Representing Numbers

First he had to devise a way to represent numbers. Unlike modern computers which use binary, so only two digits, Babbage stuck to decimal. He was going to do all his calculations using our normal ten digits, 0 – 9. But how? His solution was to use metal cog-like wheels. His wheels had 40 teeth corresponding to the digits 0 to 9 repeated four times. To get the idea of how they worked, imagine a wheel with only 10 teeth, each with a digit 0-9 in order, next to a tooth. The wheel lays flat and one digit faces you. That digit is the number that the wheel represents. Turn it one place to the left and it represents one digit higher. Turn it a place to the right and it represents one digit lower.

One of Babbage's wheels with teeth at the bottom and digits 0 to 9 repeated round the edge abocve the teeth. Nibs (ridges) are used to drive the carry to the next wheel.

Babbage’s wheel from a 3D model by Adrian Johnstone.

That is fine for numbers between 0 and 9. For larger numbers, just do as we do: use the decimal place system where the value of a digit changes with its position. That first wheel is in the ones row so stands for 0-9. Put a wheel above it in a 10s row and it stands for 10 times the value shown. If a 5 is facing you on that wheel it stands for 50. You can now represent numbers 0 – 99. Put more wheels on top and you can represent hundreds, thousands, and so on.

It’s a neat way of representing numbers using the system we do (though our numbers run right to left not bottom to top). It makes it not only easy for a machine to manipulate the numbers by turning the wheels, but also easy for a human operator to read the numbers. His Difference Engine used several stacks of them, but Babbage envisaged a gigantic room-sized data store of column after column of these number wheels as the memory of his analytical engine, each column storing one potentially very large number.

A machine that can count

We now have a way to represent numbers but it isn’t yet enough to allow a machine to manipulate them automatically. As it stands it can’t even count properly. We have seen only how to count on one wheel, so only up to 9: every time we turn a crank the 1s wheel turns one notch and so the number represented moves on one. However, we need the other wheels to turn too, but only when the wheel below turns from a 9 to a 0 (so should really become 10). We need a mechanism to carry up to the wheel above. Babbage did this by adding a ridge (a ‘nib’) on the wheel that triggered the carry. When the wheel got to 0, the nib caught against a mechanism above and pushed it, before allowing it to spring back. That nudged the wheel above along one place as required. The 1s wheel was controlled by the crank. The 10s wheel was turned by the 1s wheel moving to 0. The 100s wheel was turned by the 10s wheel moving to 0, and so on. Babbage had a machine that could count!

A machine that can add

The next problem is how to add numbers stored on wheels. Imagine two wheels, interlocked by their teeth, When one is turned it turns the other the same amount. However if you lift one of the wheels they no longer interlock and move independently.

To do addition, the first wheel is used to hold the number to be added. The second holds the total so far: the answer. That answer wheel starts off set to 0. Now, with the wheels interlocked, turn the first wheel one position at a time counting up to the first number of the addition. It turns the answer wheel exactly the same number of positions transferring the number on to it.

Oops. When cogs interlock, the second wheel turns in the opposite direction to the first! Our machine is subtracting! To make it add, you need a connecting wheel between them. The middle wheel then turns backwards, turning the answer wheel forwards as required. With three wheels like this, any number on the first wheel is added to the answer wheel.

To add a second number, just lift the first wheel to disconnect it, spin it back to zero, drop it back in place and turn it to the second number. The answer wheel then holds the sum of both numbers. If you want to add more numbers, just keep doing this, loading one number at a time onto the first wheel. Each time the total passes 10, the carry mechanism passes the 10 onto the higher wheel and the full decimal total is stored up the stack of wheels.

We have a machine for doing addition!

A machine that can multiply

Babbage’s machines could multiply as well. How do you do multiplication on wheels? Well, multiplication is just repeated addition. If you want to work out 5 x 3, then it can be calculated as 5 + 5 + 5. So multiplication can simply be done using the adder, adding the same number over and over again. A counter keeps track of how many times to add it. There are faster ways to multiply though. For the Analytical Engine, Babbage designed an efficient table-based multiplier that he was justifiably very proud of.

Putting it together

Put this together and you have both a number store (a computer memory) and temporary storage areas (registers). You can transfer numbers from one place to another in the machine, and you have the basics of an arithmetic unit that can do calculations. That is about as far as Babbage managed to build. However, he also envisioned programs on punch cards that determined what instruction to execute, mechanisms that allowed instructions to make decisions, and to repeat instructions…everything needed for a general-purpose computer.

Sadly, only parts of his Analytical Engine were ever built, the Victorians did not start the digital age, and we had to wait nearly a century for the first working computers.


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.

Making core rope memory

A coloured bead version of core rope memory with J encoded on its 8 beads (01001010)

by Jo Brodie, Queen Mary University of London

We have explained how core rope memory was used as the computer memory storing the Apollo guidance computer program that got us to the moon. A team from the University of Washington came up with a fun craft activity to make your own core memory. It may not fly you to the moon, but is a neat way to store information in a bracelet. Find their activity pages here [EXTERNAL].

What it involves is threading 8 beads onto a string, with a gap between them to form a storage space for bytes of data. Each byte is 8 binary bits (Eight pieces of information, each a 1 or a 0). Each bead represents the position of one bit in your core rope memory. You then take other threads and weave them through the beads. Each thread will store another byte of actual data. Pass the thread through a bead when you want that bead to read 1, or over, when you want that bead to read 0.

Each thread weaving past or through 8 beads can then encode the information for one letter. By adding lots of threads you can store a word or even a sentence on each core rope memory string (perhaps your name, or some secret message).

Using a binary encoding for each letter (so capital letter A would be the 8 bits 01000001 if you’re following this conversion from binary to letters table) you put that letter’s thread through or over each of the 8 beads to ‘spell’ out the letter in binary.

My name is Jo so a core rope memory encoding my name would have only three threads (one to hold the 8 beads and two to spell my name). The second thread would go over, through, over, over, through, over, through, over to spell the capital letter J (01001010). The second thread would go over, through, through, over, through, through, through, through to spell lowercase o (01101111).

Let’s hope you have a slightly longer name so can have more fun time creating your own personalised core rope memory!


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This article was funded by UKRI, through Professor Ursula Martin’s grant EP/K040251/2 and grant EP/W033615/1.