Let’s ask a really crazy question. As a pure intellectual exercise—not that it would ever happen—but just asking: What would it take to destroy American science? I know this is a silly question. After all, no one in their right mind would want to take down American science. It has been the guiding light in the world for the last 100 years, ushering in such technological marvels of modern life like transistors and the computer and lasers and solar panels and vaccines and immunotherapy and disease-resistant crops and such. So of course, American science is a National Treasure, more valuable than all the National Treasures in Washington, and no one would ever dream of attacking those.
But for the sake of argument, just to play Devil’s Advocate, what if someone with some power, someone who could make otherwise sensible people do his will, wanted to wash away the last 100 years of American leadership in Science? How would he do it?
The answer is obvious: Use science … and maybe even physics.
The laws of physics are really pretty simple: Cause and effect, action and reaction … those kinds of things. And modern physics is no longer about rocks thrown from cliffs, but is about the laws governing complex systems, like networks of people.
Can we really put equations to people? This was the grand vision of Isaac Asimov in his Foundation Trilogy. In that story, the number of people in a galaxy became so large that the behavior of the population as a whole could be explained by a physicist, Hari Seldon, using the laws of statistical mechanics. Asimov called it psychohistory.
It turns out we are not that far off today, and we don’t need a galaxy full of people to make it valid. But the name of the theory turns out to be a bit more prosaic than psychohistory: it’s called Network theory.
Network Theory
Network theory, at its core, is simply about nodes and links. It asks simple questions, like: What defines a community? What kind of synergy makes communities work? And when do things fall apart?
Science is a community.
In the United State, there are approximately a million scientists , 70% of whom work in industry with 20% in academia and 10% in government (at least, prior to 2025). Despite the low fraction employed in academia, all scientists and engineers received their degrees from universities and colleges and many received post-graduate training at those universities and at national labs like Los Alamos and the NIH labs in Washington. These are the backbone of the American scientific community, these are the hubs from which the vast network of scientists connect out across the full range of industrial and manufacturing activities that drive 70% of the GDP of the United States. The universities and colleges are also reservoirs for long-term science knowledge that can be tapped at a moment’s notice by industry when it pivots to new materials or new business models.
In network theory, hubs hold the key to the performance of the network. In technical terms, hubs have high average degree, which means that hubs connect to a large fraction of the total network. This is why hubs are central to network health and efficiency. Hubs also are the main cause of the “Small World Effect”, which states that everyone on a network is only a few links away from anyone else. This is also known as “Six degrees of Separation”, because in even vast networks that span the country, it only takes about 6 friends of friends of friends of friends of friends of friends before you connect to any given person. The world is small because you know someone who is a hub, and they know everyone else. This is a fundamental result of network theory, whether the network is of people, or servers, or computer chips.
Having established how important hubs are to network connectivity, it is clear that the disproportionate importance of hubs make them a disproportionate target for network disruption. For instance, in the power grid, take down a large central switching station and you can take down the grid over vast portions of the country. The same is true for science and the science community. Take down a few of the key pins, and the whole network can collapse—a topic of percolation theory.
Percolation and Collapse
Percolation theory says what it does––it tells when a path on a network is likely to “percolate” across it—like water percolating through coffee grounds. For a given number of nodes N, there needs to be enough links so that most of the nodes belong to the largest connected cluster. Then most starting paths can percolate across the whole network. On the other hand, if enough links are broken, then the network breaks apart into a lot of disconnected clusters, and you cannot get from one to the others.
Percolation theory says a lot about the percolation transition that occurs at the percolation threshold—which describes how the likelihood of having a percolating path across a network rises and falls as the number of links in the network increases or decreases. It turns out that for large networks, this transition from percolating to non-percolating is abrupt. When there are just barely enough links to keep the network connected, then removing just one link can separate it into disconnected clusters. In other words, the network collapses.
Therefore, network collapse can be sudden and severe. It is even possible to be near the critical percolation condition and not know it. All can seem fine, with plenty of paths to choose from to get across the network—then lose just a few links—and suddenly the network collapses into a bunch of islands. This is sometimes known as a tipping point—also as a bifurcation or as a catastrophe. Tipping points, bifurcations and percolation transitions get a lot of attention in network theory, because they are sudden and large events that can occur with little forewarning.
So the big question for this blog is: What would it take to have the scientific network of the United States collapse?
Department of Governmental Exterminations (DOGE)
The head of DOGE is a charismatic fellow, and like the villain of Jane Austen’s Pride and Prejudice, he was initially a likable character. But he turned out to be an arbiter of chaos and a cad. No one would want to be him in the end. The same is true in our own Austenesque story of Purge and Precipice: As DOGE purges, we approach the precipice.
Falling off a cliff is easy, because if a network has hubs, and those hubs have a disproportionate importance to keeping the network together, then an excellent strategy to destroy the network would be to randomly take out the most important hubs.
If the hubs of the scientific network across the US are the universities and colleges and government labs, then attack those, even though they only hold 20% to 30% of the scientists in the country, you can bring science to a standstill in the US by breaking apart the network into isolate islands. Alternatively, when talking about individuals in a network, the most important hubs are the scientists who are the repositories of the most knowledge—the elder statesmen of their fields—the ones you can get to buy out and retire.
Networks with strongly connected hubs are the most vulnerable to percolation collapse when the hubs are attacked specifically.
Science Network Evolving under Reduction in Force through Natural Attrition
Fig. 1 Healthy network evolving under a 15% reduction in force (RIF) through natural retirement and attrition.
This simulation looks at a reduction in force (RIF) of 15% and its effect on a healthy interaction network. It uses a scale-free network that evolves in time as individuals retire naturally or move to new jobs. When a node is removed from the net, it becomes a disconnected dot in the video. Other nodes that were “orphaned” by the retirement are reassigned to existing nodes. Links represent scientific interactions or lines of command. A few links randomly shift as interests change. Random retirements might hit a high-degree node (a hub), but the event is rare enough that the natural rearrangements of the links continue to keep the network connected and healthy as it adapts to the loss of key opinion leaders.
Science Network under DOGE Attack
Fig. 2 An attack on the high-degree nodes (the hubs) of the network, leading to the same 15% RIF as Fig. 1. The network becomes fragmented and dysfunctional.
Universities and government laboratories are high-degree nodes that have a disproportionate importance to the Science Network. By targeting these nodes, the network rapidly disintegrates. The effect is too drastic for the rearrangement of some links to fix it.
The percolation probability of an interaction network, like the Science Network, is a fair measure of scientific productivity. The more a network is interconnected, the more ideas flow across the web, eliciting new ideas and discoveries that often lead to new products and growth in the national GDP. But a disrupted network has low productivity. The scientific productivity is plotted in Fig. 3 as a function of the reduction in force up to 15%. Natural attrition can attain this RIF with minimal impact on the productivity of the network measured through its percolation probability. However, targeted attacks on the most influential scientific hubs rapidly degrades the network, breaking it apart into lots of disconnected clusters. There is no free flow of ideas and lost opportunities for new products and eventual erosion of the national GDP.
Fig. 3 Scientific productivity, measured by the percolation probability across the network, as a function of the reduction in force up to 15%. Natural attrition keeps most of the productivity high. Targeted attacks on the most influential science institutions decimate the Science Network.
It takes about 15 years for scientific discoveries to establish new products in the market place. Therefore, a collapse of American science over the next few years won’t be fully felt until around the year 2040. All the politicians in office today will be long gone by then (let’s hope!), so they will never get the blame. But our country will be poorer and weaker, and our lives will be poorer and sicker—the victims of posturing and grandstanding for no real benefit other than the fleeting joy of wrecking what was built over the past century. When I watch the glee of the Perp in Chief and his henchmen as they wreak their havoc, I am reminded of “griefers” in Minecraft.
The Upshot
One of the problems with being a physicist is that sometimes you see the train wreck coming.
I see a train wreck coming.
PostScript
It is important not to take these simulations too literally as if they were an accurate numerical model of the Science Network in the US. The point of doing physics is not to fit all the parameters—that’s for the engineers. The point of doing physics is to recognize the possibilities and to see the phenomena—as well as the dangers.
Take heed of the precipice. It is real. Are we about to go over it? It’s hard to tell. But should we even take the chance?
Something strange almost happened in 1840’s England just a few years into Queen Victoria’s long reign—a giant machine the size of a large shed, built of thousands of interlocking steel gears, driven by steam power, almost came to life—a thinking, mechanical automaton, the very image of Cyber Steampunk.
Cyber Steampunk is a genre of media that imagines an alternate history of a Victorian Age with advanced technology—airships and rockets and robots and especially computers—driven by steam power. Some of the classics that helped launch the genre are the animé movies Castle in the Sky (1986) by Hayao Miyazaki and Steam Boy (2004) by Katsuhiro Otomo and the novel The Difference Engine (1990) by William Gibson and Bruce Sterling. The novel pursues Ada Byron, Lady Lovelace, through the shadows of London by those who suspect she has devised a programmable machine that can win at gambling using steam and punched cards. This is not too far off from what might have happened in real life if Ada Lovelace had a bit more sway over one of her unsuitable suitors—Charles Babbage.
But Babbage, part genius, part fool, could not understand what Lovelace understood—for if he had, a Victorian computer built of oiled gears and leaky steam pipes, instead of tiny transistors and metallic leads, might have come a hundred years early as another marvel of the already marvelous Industrial Revolution. How might our world today be different if Babbage had seen what Lovelace saw?
There is no question of Babbage’s genius. He was so far ahead of his time that he appeared to most people in his day to be a crackpot, and he was often treated as one. His father thought he was useless, and he told him so, because to be a scientist in the early 1800’s was to be unemployable, and Babbage was unemployed for years after college. Science was, literally, natural philosophy, and no one hired a philosopher unless they were faculty at some college. But Babbage’s friends from Trinity College, Cambridge, like William Whewell (future dean of Trinity) and John Herschel (son of the famous astronomer), new his worth and were loyal throughout their lives and throughout his trials.
Fig. 2 Charles Babbage
Charles Babbage was a favorite at Georgian dinner parties because he was so entertaining to watch and to listen to. From personal letters of his friends (and enemies) of the time one gets a picture of a character not too different from Sheldon Cooper on the TV series The Big Bang Theory—convinced of his own genius and equally convinced of the lack of genius of everyone else and ready to tell them so. His mind was so analytic, that he talked like a walking computer—although nothing like a computer existed in those days—everything was logic and functions and propositions—hence his entertainment value. No one understood him, and no one cared—until he ran into a young woman who actually did, but more of that later.
One summer day in 1821, Babbage and Herschel were working on mathematical tables for the Astrophysical Society, a dull but important job to ensure that star charts and moon positions could be used accurately for astronomical calculations and navigation. The numbers filled column after column, page after page. But as they checked the values, the two were shocked by how many entries in the tables were wrong. In that day, every numerical value of every table or chart was calculated by a person (literally called a computer), and people make mistakes. Even as they went to correct the numbers, new mistakes would crop in. In frustration, Babbage exclaimed to Herschel that what they needed was a steam-powered machine that would calculate the numbers automatically. No sooner had he said it, than Babbage had a vision of a mechanical machine, driven by a small steam engine, full of gears and rods, that would print out the tables automatically without flaws.
Being unemployed (and unemployable) Babbage had enough time on his hands to actually start work on his engine. He called it the Difference Engine because it worked on the Method of Differences—mathematical formulas were put into a form where a number was expressed as a series, and the differences between each number in the series would be calculated by the engine. He approached the British government for funding, and it obliged with considerable funds. In the days before grant proposals and government funding, Babbage had managed to jump start his project and, in a sense, gain employment. His father was not impressed, but he did not live long enough to see what his son Charles could build. Charles inherited a large sum from his father (the equivalent of about 14 million dollars today), which further freed him to work on his Difference Engine. By 1832, he had finally completed a seventh part of the Engine and displayed it in his house for friends and visitors to see.
This working section of the Difference Engine can be seen today in the London Science Museum. It is a marvel of steel and brass, consisting of three columns of stacked gears whose enmeshed teeth represent digital numbers. As a crank handle is turned, the teath work upon each other, generating new numbers through the permutations of rotated gear teeth. Carrying tens was initially a problem for Babbage, as it is for school children today, but he designed an ingenious mechanical system to accomplish the carry.
All was going well, and the government was pleased with progress, until Charles had a better idea that threatened to scrap all he had achieved. It is not known how this new idea came into being, but it is known that it happened shortly after he met the amazing young woman: Ada Byron.
Lovely Lovelace
Ada Lovelace, born Ada Byron, had the awkward distinction of being the only legitimate child of Lord Byron, lyric genius and poet. Such was Lord Byron’s hedonist lifestyle that no-one can say for sure how many siblings Ada had, not even Lord Byron himself, which was even more awkward when his half-sister bore a bastard child that may have been his.
Fig. 4 Ada Lovelace
Ada’s high-born mother prudently divorced the wayward poet and was not about to have Ada pulled into her father’s morass. Where Lord Byron was bewitched (some would say possessed) by art and spirit, the mother sought an antidote, and she encouraged Ada to study hard cold mathematics. She could not have known that Ada too had a genius like her father’s, only aimed differently, bewitched by the beauty in the sublime symbols of math.
An insight into the precocious child’s way of thinking can be gained from a letter that the 12-year-old girl wrote to her mother who was off looking for miracle cures for imaginary ills. At that time in 1828, in a confluence of historical timelines in the history of mathematics, Ada and her mother (and Ada’s cat Puff) were living at Bifrons House which was the former estate of Brook Taylor, who had developed the Taylor’s series a hundred years earlier in 1715. In Ada’s letter, she describes a dream she had of a flying machine, which is not so remarkable, but then she outlined her plan to her mother to actually make one, which is remarkable. As you read her letter, you see she is already thinking about weights and material strengths and energy efficiencies, thinking like an engineer and designer—at the age of only 12 years!
In later years, Lovelace would become the Enchantress of Number to a number of her mathematical friends, one of whom was the strange man she met at a dinner party in the summer of 1833 when she was 17 years old. The strange man was Charles Babbage, and when he talked to her about his Difference Engine, expecting to be tolerated as an entertaining side show, she asked pertinent questions, one after another, and the two became locked in conversation.
Babbage was a recent widower, having lost his wife with whom he had been happily compatible, and one can only imagine how he felt when the attractive and intelligent woman gave him her attention. But Ada’s mother would never see Charles as a suitable husband for her daughter—she had ambitious plans for her, and she tolerated Babbage only as much as she did because of the affection that Ada had for him. Nonetheless, Ada and Charles became very close as friends and met frequently and wrote long letters to each other, discussing problems and progress on the Difference Engine.
In December of 1834, Charles invited Lady Byron and Ada to his home where he described with great enthusiasm a vision he had of an even greater machine. He called it his Analytical Engine, and it would surpass his Difference Engine in a crucial way: where the Difference Engine needed to be reconfigured by hand before every new calculation, the Analytical Engine would never need to be touched, it just needed to be programmed with punched cards. Charles was in top form as he wove his narrative, and even Lady Byron was caught up in his enthusiasm. The effect on Ada, however, was nothing less than a religious conversion.
Fig. 5 General block diagram of Babbage’s Analytical Engine. From [8].
Ada’s Notes
To meet Babbage as an equal, Lovelace began to study mathematics with an obsession, or one might say, with delusions of grandeur. She wrote “I believe myself to possess a most singular combination of qualities exactly fitted to make me pre-eminently a discoverer of the hidden realities of nature,” and she was convinced that she was destined to do great things.
Then, in 1835, Ada was married off to a rich but dull aristocrat who was elevated by royal decree to the Earldom of Lovelace, making her the Countess of Lovelace. The marriage had little effect on Charles’ and Ada’s relationship, and he was invited frequently to the new home where they continued their discussions about the Analytical Engine.
By this time Charles had informed the British government that he was putting all his effort into the design his new machine—news that was not received favorably since he had never delivered even a working Difference Engine. Just when he hoped to start work on his Analytical Engine, the government ministers pulled their money. This began a decade’s long ordeal for Babbage as he continued to try to get monetary support as well as professional recognition from his peers for his ideas. Neither attempt was successful at home in Britain, but he did receive interest abroad, especially from a future prime minister of Italy, Luigi Menabrae, who invited Babbage to give a lecture in Turin on his Analytical Engine. Menabrae later had the lecture notes published in French. When Charles Wheatstone, a friend of Babbage, learned of Menabrae’s publication, he suggested to Lovelace that she translate it into English. Menabrae’s publication was the only existing exposition of the Analytical Engine, because Babbage had never written on the Engine himself, and Wheatstone was well aware of Lovelace’s talents, expecting her to be one of the only people in England who had the ability and the connections to Babbage to accomplish the task.
Ada Lovelace dove into the translation of Menabrae’s “Sketch of the Analytical Engine Invented by Charles Babbage” with the single-mindedness that she was known for. Along with the translation, she expanded on the work with Notes of her own that she added, lettered from A to G. By the time she wrote them, Lovelace had become a top-rate mathematician, possibly surpassing even Babbage, and her Notes were three times longer than the translation itself, providing specific technical details and mathematical examples that Babbage and Menabrae only allude to.
On a different level, the character of Ada’s Notes stands in stark contrast to Charles’ exposition as captured by Menabrae: where Menabrae provided only technical details of Babbage’s Engine, Lovelace’s Notes captured the Engine’s potential. She was still a poet by disposition—that inheritance from her father was never lost.
Lovelace wrote:
We may say most aptly, that the Analytical Engine weaves algebraic patterns just as the Jacquard-loom weaves flowers and leaves.
Here she is referring to the punched cards that the Jacquard loom used to program the weaving of intricate patterns into cloth. Babbage had explicitly borrowed this function from Jacquard, adapting it to provide the programmed input to his Analytical Engine.
But it was not all poetics. She also saw the abstract capabilities of the Engine, writing
In studying the action of the Analytical Engine, we find that the peculiar and independent nature of the considerations which in all mathematical analysis belong to operations, as distinguished from the objects operated upon and from the results of the operations performed upon those objects, is very strikingly defined and separated.
Again, it might act upon other things besides number, where objects found whose mutual fundamental relations could be expressed by those of the abstract science of operations, and which should be also susceptible of adaptations to the action of the operating notation and mechanism of the engine.
Supposing, for instance, that the fundamental relations of pitched sounds in the science of harmony and of musical composition were susceptible of such expression and adaptations, the engine might compose elaborate and scientific pieces of music of any degree of complexity or extent.
Here she anticipates computers generating musical scores.
Most striking is Note G. This is where she explicitly describes how the Engine would be used to compute numerical values as solutions to complicated problems. She chose, as her own example, the calculation of Bernoulli numbers which require extensive numerical calculations that were exceptionally challenging even for the best human computers of the day. In Note G, Lovelace writes down the step-by-step process by which the Engine would be programmed by the Jacquard cards to carry out the calculations. In the history of computer science, this stands as the first computer program.
Fig. 6 Table from Lovelace’s Note G on her method to calculate Bernoulli numbers using the Analytical Engine.
When it was time to publish, Babbage read over Lovelace’s notes, checking for accuracy, but he appears to have been uninterested in her speculations, possibly simply glossing over them. He saw his engine as a calculating machine for practical applications. She saw it for what we know today to be the exceptional adaptability of computers to all realms of human study and activity. He did not see what she saw. He was consumed by his Engine to the same degree as she, but where she yearned for the extraordinary, he sought funding for the mundane costs of machining and materials.
Ada’s Business Plan Pitch
Ada Lovelace watched in exasperation as Babbage floundered about with ill-considered proposals to the government while making no real progress towards a working Analytical Engine. Because of her vision into the potential of the Engine, a vision that struck her to her core, and seeing a prime opportunity to satisfy her own yearning to make an indelible mark on the world, she despaired in ever seeing it brought to fruition. Charles, despite his genius, was too impractical, wasting too much time on dead ends and incapable of performing the deft political dances needed to attract support. She, on the other hand, saw the project clearly and had the time and money and the talent, both mathematically and through her social skills, to help.
On Monday August 14, 1843, Ada wrote what might be the most heart-felt and impassioned business proposition in the history of computing. She laid out in clear terms to Charles how she could advance the Analytical Engine to completion if only he would surrender to her the day-to-day authority to make it happen. She was, in essence, proposing to be the Chief Operating Officer in a disruptive business endeavor that would revolutionize thinking machines a hundred years before their time. She wrote (she liked to underline a lot):
“Firstly: I want to know whether if I continue to work on & about your own great subject, you will undertake to abide wholly by the judgment of myself (or of any persons whom you may now please to name as referees, whenever we may differ), on all practical matters relating to whatever can involve relations with any fellow-creature or fellow-creatures.
Secondly: can you undertake to give your mind wholly & undividedly, as a primary object that no engagement is to interfere with, to the consideration of all those matters in which I shall at times require your intellectual assistance & supervision; & can you promise not to slur & hurry things over; or to mislay, & allow confusion and mistakes to enter into documents, &c?
Thirdly: if I am able to lay before you in the course of a year or two, explicit & honorable propositions for executing your engine, (such as are approved by persons whom you may now name to be referred to for their approbation), would there be any chance of your allowing myself & such parties to conduct the business for you; your own undivided energies being devoted to the execution of the work; & all other matters being arranged for you on terms which your own friends should approve?“
This is a remarkable letter from a self-possessed 28-year-old woman, laying out in explicit terms how she proposed to take on the direction of the project, shielding Babbage from the problems of relating to other people or “fellow-creatures” (which was his particular weakness), giving him time to focus his undivided attention on the technical details (which was his particular strength), while she would be the outward face of the project that would attract the appropriate funding.
In her preface to her letter, Ada adroitly acknowledges that she had been a romantic disappointment to Charles, but she pleads with him not to let their personal history cloud his response to her proposal. She also points out that her keen intellect would be an asset to the project and asks that he not dismiss it because of her sex (which a biased Victorian male would likely do). Despite her entreaties, this is exactly what Babbage did. Pencilled on the top of the original version of Ada’s letter in the Babbage archives is his simple note: “Tuesday 15 saw AAL this morning and refused all the conditions”. He had not even given her proposal 24 hours consideration as he indeed slurred and hurried things over.
Aftermath
Babbage never constructed his Analytical Engine and never even wrote anything about it. All his efforts would have been lost to history if Alan Turing had not picked up on Ada’s Notes and expanded upon them a hundred years later, bringing both her and him to the attention of the nascent computing community.
Ada Lovelace died young in 1852, at the age of 36, of cancer. By then she had moved on from Babbage and was working on other things. But she never was able to realize her ambition of uncovering such secrets of nature as to change the world.
Ada had felt from an early age that she was destined for greatness. She never achieved it in her lifetime and one can only wonder what she thought about this as she faced her death. Did she achieve it in posterity? This is a hotly debated question. Some say she wrote the first computer program, which may be true, but little programming a hundred years later derived directly from her work. She did not affect the trajectory of computing history. Discovering her work after the fact is interesting, but cannot be given causal weight in the history of science. The Vikings were the first Europeans to discover America, but no-one knew about it. They did not affect subsequent history the way that Columbus did.
On the other hand, Ada has achieved greatness in a different way. Now that her story is known, she stands as an exemplar of what scientific and technical opportunities look like, and the risk of ignoring them. Babbage also did not achieve greatness during his lifetime, but he could have—if he had not dismissed her and her intellect. He went to his grave embittered rather than lauded because he passed up an opportunity he never recognized.
When Galileo trained his crude telescope on the planet Jupiter, hanging above the horizon in 1610, and observed moons orbiting a planet other than Earth, it created a quake whose waves have rippled down through the centuries to today. Never had such hard evidence been found that supported the Copernican idea of non-Earth-centric orbits, freeing astronomy and cosmology from a thousand years of error that shaded how people thought.
The Earth, after all, was not the center of the Universe.
Galileo’s moons: the Galilean Moons—Io, Europa, Ganymede, and Callisto—have drawn our eyes skyward now for over 400 years. They have been the crucible for numerous scientific discoveries, serving as a test bed for new ideas and new techniques, from the problem of longitude to the speed of light, from the birth of astronomical interferometry to the beginnings of exobiology. Here is a short history of Galileo’s Moons in the history of physics.
Galileo (1610): Celestial Orbits
In late 1609, Galileo (1564 – 1642) received an unwelcome guest to his home in Padua—his mother. She was not happy with his mistress, and she was not happy with his chosen profession, but she was happy to tell him so. By the time she left in early January 1610, he was yearning for something to take his mind off his aggravations, and he happened to point his new 20x telescope in the direction of the planet Jupiter hanging above the horizon [1]. Jupiter appeared as a bright circular spot, but nearby were three little stars all in line with the planet. The alignment caught his attention, and when he looked again the next night, the position of the stars had shifted. On successive nights he saw them shift again, sometimes disappearing into Jupiter’s bright disk. Several days later he realized that there was a fourth little star that was also behaving the same way. At first confused, he had a flash of insight—the little stars were orbiting the planet. He quickly understood that just as the Moon orbited the Earth, these new “Medicean Planets” were orbiting Jupiter. In March 1610, Galileo published his findings in Siderius Nuncius (The Starry Messenger).
Page from Galileo’s Starry Messenger showing the positions of the moon of Jupiter
It is rare in the history of science for there not to be a dispute over priority of discovery. Therefore, by an odd chance of fate, on the same nights that Galileo was observing the moons of Jupiter with his telescope from Padua, the German astronomer Simon Marius (1573 – 1625) also was observing them through a telescope of his own from Bavaria. It took Marius four years to publish his observations, long after Galileo’s Siderius had become a “best seller”, but Marius took the opportunity to claim priority. When Galileo first learned of this, he called Marius “a poisonous reptile” and “an enemy of all mankind.” But harsh words don’t settle disputes, and the conflicting claims of both astronomers stood until the early 1900’s when a scientific enquiry looked at the hard evidence. By that same odd chance of fate that had compelled both men to look in the same direction around the same time, the first notes by Marius in his notebooks were dated to a single day after the first notes by Galileo! Galileo’s priority survived, but Marius may have had the last laugh. The eternal names of the “Galilean” moons—Io, Europe, Ganymede and Callisto—were given to them by Marius.
Picard and Cassini (1671): Longitude
The 1600’s were the Age of Commerce for the European nations who relied almost exclusively on ships and navigation. While latitude (North-South) was easily determined by measuring the highest angle of the sun above the southern horizon, longitude (East-West) relied on clocks which were notoriously inaccurate, especially at sea.
The Problem of Determining Longitude at Sea is the subject of Dava Sobel’s thrilling book Longitude (Walker, 1995) [2] where she reintroduced the world to what was once the greatest scientific problem of the day. Because almost all commerce was by ships, the determination of longitude at sea was sometimes the difference between arriving safely in port with a cargo or being shipwrecked. Galileo knew this, and later in his life he made a proposal to the King of Spain to fund a scheme to use the timings of the eclipses of his moons around Jupiter to serve as a “celestial clock” for ships at sea. Galileo’s grant proposal went unfunded, but the possibility of using the timings of Jupiter’s moons for geodesy remained an open possibility, one which the King of France took advantage of fifty years later.
In 1671 the newly founded Academie des Sciences in Paris funded an expedition to the site of Tycho Brahe’s Uranibourg Observatory in Hven, Denmark, to measure the time of the eclipses of the Galilean moons observed there to be compared the time of the eclipses observed in Paris by Giovanni Cassini (1625 – 1712). When the leader of the expedition, Jean Picard (1620 – 1682), arrived in Denmark, he engaged the services of a local astronomer, Ole Rømer (1644 – 1710) to help with the observations of over 100 eclipses of the Galilean moon Io by the planet Jupiter. After the expedition returned to France, Cassini and Rømer calculated the time differences between the observations in Paris and Hven and concluded that Galileo had been correct. Unfortunately, observing eclipses of the tiny moon from the deck of a ship turned out not to be practical, so this was not the long-sought solution to the problem of longitude, but it contributed to the early science of astrometry (the metrical cousin of astronomy). It also had an unexpected side effect that forever changed the science of light.
Ole Rømer (1676): The Speed of Light
Although the differences calculated by Cassini and Rømer between the times of the eclipses of the moon Io between Paris and Hven were small, on top of these differences was superposed a surprisingly large effect that was shared by both observations. This was a systematic shift in the time of eclipse that grew to a maximum value of 22 minutes half a year after the closest approach of the Earth to Jupiter and then decreased back to the original time after a full year had passed and the Earth and Jupiter were again at their closest approach. At first Cassini thought the effect might be caused by a finite speed to light, but he backed away from this conclusion because Galileo had shown that the speed of light was unmeasurably fast, and Cassini did not want to gainsay the old master.
Ole Rømer
Rømer, on the other hand, was less in awe of Galileo’s shadow, and he persisted in his calculations and concluded that the 22 minute shift was caused by the longer distance light had to travel when the Earth was farthest away from Jupiter relative to when it was closest. He presented his results before the Academie in December 1676 where he announced that the speed of light, though very large, was in fact finite. Unfortnately, Rømer did not have the dimensions of the solar system at his disposal to calculate an actual value for the speed of light, but the Dutch mathematician Huygens did.
When Christian Huygens read the proceedings of the Academie in which Rømer had presented his findings, he took what he knew of the radius of Earth’s orbit and the distance to Jupiter and made the first calculation of the speed of light. He found a value of 220,000 km/second (kilometers did not exist yet, but this is the equivalent of what he calculated). This value is 26 percent smaller than the true value, but it was the first time a number was given to the finite speed of light—based fundamentally on the Galilean moons. For a popular account of the story of Picard and Rømer and Huygens and the speed of light, see Ref. [3].
Michelson (1891): Astronomical Interferometry
Albert Michelson (1852 – 1931) was the first American to win the Nobel Prize in Physics. He received the award in 1907 for his work to replace the standard meter, based on a bar of metal housed in Paris, with the much more fundamental wavelength of red light emitted by Cadmium atoms. His work in Paris came on the heels of a new and surprising demonstration of the use of interferometry to measure the size of astronomical objects.
Albert Michelson
The wavelength of light (a millionth of a meter) seems ill-matched to measuring the size of astronomical objects (thousands of meters) that are so far from Earth (billions of meters). But this is where optical interferometry becomes so important. Michelson realized that light from a distant object, like a Galilean moon of Jupiter, would retain some partial coherence that could be measured using optical interferometry. Furthermore, by measuring how the interference depended on the separation of slits placed on the front of a telescope, it would be possible to determine the size of the astronomical object.
From left to right: Walter Adams, Albert Michelson, Walther Mayer, Albert Einstein, Max Ferrand, and Robert Milliken. Photo taken at Caltech.
In 1891, Michelson traveled to California where the Lick Observatory was poised high above the fog and dust of agricultural San Jose (a hundred years before San Jose became the capitol of high-tech Silicon Valley). Working with the observatory staff, he was able to make several key observations of the Galilean moons of Jupiter. These were just close enough that their sizes could be estimated (just barely) from conventional telescopes. Michelson found from his calculations of the interference effects that the sizes of the moons matched the conventional sizes to within reasonable error. This was the first demonstration of astronomical interferometry which has burgeoned into a huge sub-discipline of astronomy today—based originally on the Galilean moons [4].
Pioneer (1973 – 1974): The First Tour
Pioneer 10 was launched on March 3, 1972 and made its closest approach to Jupiter on Dec. 3, 1973. Pioneer 11 was launched on April 5, 1973 and made its closest approach to Jupiter on Dec. 3, 1974 and later was the first spacecraft to fly by Saturn. The Pioneer spacecrafts were the first to leave the solar system (there have now been 5 that have left, or will leave, the solar system). The cameras on the Pioneers were single-pixel instruments that made line-scans as the spacecraft rotated. The point light detector was a Bendix Channeltron photomultiplier detector, which was a vacuum tube device (yes vacuum tube!) operating at a single-photon detection efficiency of around 10%. At the time of the system design, this was a state-of-the-art photon detector. The line scanning was sufficient to produce dramatic photographs (after extensive processing) of the giant planets. The much smaller moons were seen with low resolution, but were still the first close-ups ever to be made of Galileo’s moons.
Voyager (1979): The Grand Tour
Voyager 1 was launched on Sept. 5, 1977 and Voyager 2 was launched on August 20, 1977. Although Voyager 1 was launched second, it was the first to reach Jupiter with closest approach on March 5, 1979. Voyager 2 made its closest approach to Jupiter on July 9, 1979.
In the Fall of 1979, I had the good fortune to be an undergraduate at Cornell University when Carl Sagan gave an evening public lecture on the Voyager fly-bys, revealing for the first time the amazing photographs of not only Jupiter but of the Galilean Moons. Sitting in the audience listening to Sagan, a grand master of scientific story telling, made you feel like you were a part of history. I have never been so convinced of the beauty and power of science and technology as I was sitting in the audience that evening.
The camera technology on the Voyagers was a giant leap forward compared to the Pioneer spacecraft. The Voyagers used cathode ray vidicon cameras, like those used in television cameras of the day, with high-resolution imaging capabilities. The images were spectacular, displaying alien worlds in high-def for the first time in human history: volcanos and lava flows on the moon of Io; planet-long cracks in the ice-covered surface of Europa; Callisto’s pock-marked surface; Ganymede’s eerie colors.
The Voyager’s discoveries concerning the Galilean Moons were literally out of this world. Io was discovered to be a molten planet, its interior liquified by tidal-force heating from its nearness to Jupiter, spewing out sulfur lava onto a yellowed terrain pockmarked by hundreds of volcanoes, sporting mountains higher than Mt. Everest. Europa, by contrast, was discovered to have a vast flat surface of frozen ice, containing no craters nor mountains, yet fractured by planet-scale ruptures stained tan (for unknown reasons) against the white ice. Ganymede, the largest moon in the solar system, is a small planet, larger than Mercury. The Voyagers revealed that it had a blotchy surface with dark cratered patches interspersed with light smoother patches. Callisto, again by contrast, was found to be the most heavily cratered moon in the solar system, with its surface pocked by countless craters.
Galileo (1995): First in Orbit
The first mission to orbit Jupiter was the Galileo spacecraft that was launched, not from the Earth, but from Earth orbit after being delivered there by the Space Shuttle Atlantis on Oct. 18, 1989. Galileo arrived at Jupiter on Dec. 7, 1995 and was inserted into a highly elliptical orbit that became successively less eccentric on each pass. It orbited Jupiter for 8 years before it was purposely crashed into the planet (to prevent it from accidentally contaminating Europa that may support some form of life).
Galileo made many close passes to the Galilean Moons, providing exquisite images of the moon surfaces while its other instruments made scientific measurements of mass and composition. This was the first true extended study of Galileo’s Moons, establishing the likely internal structures, including the liquid water ocean lying below the frozen surface of Europa. As the largest body of liquid water outside the Earth, it has been suggested that some form of life could have evolved there (or possibly been seeded by meteor ejecta from Earth).
Juno (2016): Still Flying
The Juno spacecraft was launched from Cape Canaveral on Aug. 5, 2011 and entered a Jupiter polar orbit on July 5, 2016. The mission has been producing high-resolution studies of the planet. The mission was extended in 2021 to last to 2025 to include several close fly-bys of the Galilean Moons, especially Europa, which will be the object of several upcoming missions because of the possibility for the planet to support evolved life. These future missions include NASA’s Europa Clipper Mission, the ESA’s Jupiter Icy Moons Explorer, and the Io Volcano Observer.
Epilog (2060): Colonization of Callisto
In 2003, NASA identified the moon Callisto as the proposed site of a manned base for the exploration of the outer solar system. It would be the next most distant human base to be established after Mars, with a possible start date by the mid-point of this century. Callisto was chosen because it is has a low radiation level (being the farthest from Jupiter of the large moons) and is geologically stable. It also has a composition that could be mined to manufacture rocket fuel. The base would be a short-term way-station (crews would stay for no longer than a month) for refueling before launching and using a gravity assist from Jupiter to sling-shot spaceships to the outer planets.
By David D. Nolte, May 29, 2023
[1] See Chapter 2, A New Scientist: Introducing Galileo, in David D. Nolte, Galileo Unbound (Oxford University Press, 2018).
[2] Dava Sobel, Longitude: The True Story of a Lone Genius who Solved the Greatest Scientific Problem of his Time (Walker, 1995)
[3] See Chap. 1, Thomas Young Polymath: The Law of Interference, in David D. Nolte, Interference: The History of Optical Interferometry and the Scientists who Tamed Light (Oxford University Press, 2023)
[4] See Chapter 5, Stellar Interference: Measuring the Stars, in David D. Nolte, Interference: The History of Optical Interferometry and the Scientists who Tamed Light (Oxford University Press, 2023).
Read more in Books by David Nolte at Oxford University Press
Galileo Unbound 