Changing the Rules

Is the Large Hadron Collider a time machine?

Although I usually like Dennis Overbye's physics writing for the New York Times, I thought he misfired in answering this question yesterday, in the general-audience "Week in Review" section.

In a Q&A entitled A Primer on the Great Proton Smashup that discussed the scientific ideas that underlie research at the LHC, Overbye addressed the question:

"What does it mean to say that the collider will allow physicists to go back to the Big Bang? Is the collider a time machine?"

It may seem silly, but it's actually a good question, since I'd bet a lot of people get confused by the metaphors that writers use to motivate the research. These metaphors get repeated often enough that they are almost cliché, but, as with all metaphors, it's important to know which parts to take seriously and which parts are more poetic or even misleading. Not everybody will know which is which, and it's good to explain it every so often.

Here's Overbye's complete answer:

"Physicists suspect that the laws of physics evolved as the universe cooled from billions or trillions of degrees in the first moments of the Big Bang to superfrigid temperatures today (3 degrees Kelvin) — the way water changes from steam to liquid to ice as temperatures decline. As the universe cooled, physicists suspect, everything became more complicated. Particles and forces once indistinguishable developed their own identities, the way Spanish, French and Italian diverged from the original Latin.

By crashing together subatomic particles — protons — physicists create little fireballs that revisit the conditions of these earlier times and see what might have gone on back then, sort of like the scientists in Jurassic Park reincarnating dinosaurs."

I'll discuss in a moment what I think Overbye means by "the laws of physics evolved," but this notion is awfully subtle for a general reader. More importantly, it completely undercuts the whole thrust of the question: physicists believe they are learning about the early universe in high-energy particle collisions precisely because the laws of physics are the same. If the laws are the same, we can create the same conditions (mostly temperature) to learn about what might have happened in the early universe. (He eventually does say that.)

The confusion comes because the phrase "the laws of physics" can be mean quite different things.

In the context of LHC, it seems clear to me that we refer to the behavior at the deepest levels of the universe. These rules don't get repealed overnight.

In fact, as I understand the phrase, it refers not to the current human description of events, which changes as we learn more, but to the "truth," which doesn't. Otherwise, it wouldn't make sense to say that we want to learn about the laws of physics from the collider (since we already know the laws, even if they're wrong).

Still, we often say the laws of physics say that something is impossible. In that context, the phrase can only refer to our current understanding of the laws, as best as we can discern them.

In fact, when we talk about the laws of physics we're frequently not talking about the deep levels probed by the LHC. Instead, we're referring to laws that describe the more mundane behavior of objects in our cold everyday reality.

In one sense, these "laws" are just a manifestation of the deeper laws. Describing the world in terms of protons, or nuclei, or atoms, or molecules, or cells, or organs, or organisms, or societies, is often vastly more useful than describing it with quarks or strings.

In some cases, the higher-level description can be mathematically related to the deeper description, for example by "coarse graining" the description to smooth out fine details.

This is the sense in which we can say that the "laws of physics" evolve: when the universe was very hot, the description had to include a lot of ingredients that are no longer important now that the universe is much cooler. We can now accurately describe things using a simplified description that doesn't have to include the messier details. The "laws" are different now.

This is Overbye's answer. But I think it will confuse people, since the goal of the LHC is to learn about the immutable laws, not the simpler descriptions or approximations.

One further, mind-blowing complication. Many cosmologists are exploring the possibility that our universe is just one of an infinite number of universes that formed, like bubbles, out of a larger multiverse. According to this view, the "laws of physics" --perhaps even the dimension of space--may be entirely different in each of these universes.

Even if we will always see the laws of physics as unchanging, they may be not be the same everywhere.

 

 

Picturing Quantum Mechanics

They say a picture is worth a thousand words. But what if those words are wrong?

Very cool recent experiments demonstrated a chemical reaction between molecules below a millionth of a degree (in Science, subscription required). My latest story for Physical Review Focus describes theoretical modeling of this reaction. We accompanied the story with this picture from the news release issued by the Joint Quantum Institute (a partnership between the National Institute of Standards and Technology and the University of Maryland), where the work was done.

It's a pretty picture, with its superhero color scheme and all, and it satisfies our need to avoid a solid block of text. But although it might not be a bad illustration of a room-temperature chemical reaction, it distorts much of what makes these ultra-low-temperature reactions special.

It's clear in the picture that two diatomic molecules are approaching each other, with dramatic consequences in store. The details of how the artist represents the bonds connecting a potassium and a rubidium atom in each molecule don't bother me too much. It doesn't match either of the customary representations, which are ball-and-stick models and the more accurate space-filling models, but there's no perfect way to represent something that can never be seen with visible light. Of course everyone knows that potassium atoms are green, but we'll let that slide, too.

The really problematic part of this picture is very difficult to avoid: the molecules really aren't anywhere, in the sense the picture conveys.

As first shown by experiments at Bell Labs in 1927, matter acts as waves as well as particles. At temperatures below a millionth of a degree, the relevant wavelength for these molecules is hundreds of nanometers, which is much, much larger than the separation of molecules shown in the experiment. There is no meaning to saying that these molecules are separated by such a short distance. They are simultaneously close and far away.

One way to think about this is to invoke Heisenberg's uncertainty principle. According to this principle, if you know an object's momentum with very high precision, you can't, even in principle, know its position very accurately. For these ultracold molecules, the momentum is almost zero, with very high precision, so you can only know where it is to the nearest hundreds of nanometers.

There's a second problem, too. The picture shows the molecules with particular orientations in space. That may not seem strange, but the molecules in the experiment were prepared in the rotational "ground state," with the lowest possible energy. Like the s-orbitals of electrons in a hydrogen atom, this state is spherically symmetrical. This means that the molecule is equally likely to be pointing in any direction. This isn't the same thing as saying we don't know what direction it's pointing (even though it does). Quantum mechanics says that it has no direction, at least until an experiment requires it to.

So the reacting molecules really aren't at any particular distance from one another, and they don't have any particular orientation relative to each other. That's one of the things that makes this chemical reaction--and the theoretical description of it--so interesting.

But good luck drawing that.

 

The Language of Life

Ten years after the announcement of the draft human genome, the world of human health seems in many ways unchanged. But it is changing, in many profound ways, says Francis Collins, who led the government-funded part of the genome project and is now the director of the National Institutes of Health.

Collin's new book, The Language of Life: DNA and the Revolution in Personalized Medicine, aims to help the public to understand the changes so far, and those that are still to come. He covers a wide range of topics, but the guiding theme is the promise of "personalized medicine" that tailors treatment for each individual based on their genetic information.

As he shows in his occasional columns in Parade magazine, Collins is a skilled communicator of complex medical topics, including their ethical and personal dimensions. He steers authoritatively but caringly through challenging topics like race-based medicine. On the pros and cons of genetic screening, for example, he describes the desirability of genetic tests as a product of not just the relative and absolute changes in risk associate with a gene, but the seriousness of the disease and the availability of effective intervention.

I confess that I was worried that Collins might let his well-publicized Christian beliefs color this book (his previous book is called The Language of God). They did not. His beliefs arise a few times, for example in the context of stem cell research, but he deals with serious ethical questions with great respect for different points of view. In addition, as should be expected for any modern biomedical researcher, he repeatedly and matter-of-factly draws important insights from evolution.

On the whole, the writing is accessible to general readers, even as Collins discusses complex scientific topics. On occasion, however, he shows an academic's tolerance for complex, caveat-filled verbiage, as when he writes, "Therefore, at the time of this writing, the effort to utilize genetic analysis to optimize the treatment of depression has not yet reached the point of effective implementation." This stilted language is the exception, but he also slips into occasional jargon that might leave some readers temporarily stranded.

A trickier issue is Collins' frequent use of patient anecdotes to illustrate how genetic information can lead to better decisions. These human stories, drawn from his long research and clinical experience, certainly succeed at Collins' goal of inspiring hope for the potential of personalized medicine, as well as showing clearly what it mean to people. But the succession of optimistic stories begins to seem skewed to draw attention away from structural challenges in American medicine that could seriously undermine this potential. When Collins mentions these issues, it tends to be in careful euphemisms: "A recent study estimated that in the United States each year, more than 2 million hospitalized patients suffer serious adverse drug reactions, with more than 100,000 of those resulting in a fatal outcome."

In a similar vein, Collins describes the successful identifications of gene variants associated with macular degeneration. The fact that similar studies for other diseases have been rather disappointing doesn't seem to bother him much. Perhaps his decades in research, including the identification of the cystic fibrosis gene, have made him confident that these problems too will pass. But he comes across as a very optimistic person.

In spite of my quibbles, I think The Language of Life succeeds well at putting the omnipresent news stories about genetic advances in a useful context of individual medical choices. As a writer who covers these areas of science, I didn't learn an awful lot of new things from the book, but I think most people will, and will enjoy themselves in the process.

Mathophobia

In many fields of science and engineering, any technical argument must be formulated mathematically if it is to be taken seriously. In contrast, in popular writing--even about science and engineering--including a single equation is a known recipe for getting many readers to click on to the next story. Understanding this discordant reaction to math reveals a lot about how popular and technical writing differ.

Back in 2003, when I was thinking about morphing from a practicing scientist into a science writer, I seriously questioned how I could possible to explain scientific arguments without variables and equations. Without the precision of a mathematical description, I wondered, how could I really know whether readers interpreted ordinary English phrases the way I intended? Moreover, without a algebraic description, how could readers judge how well a model matches observations?

Interestingly, in the years since, I've almost never felt hobbled by not being able to explain things with equations.

A lot of the difference arises from the different goals of journal articles and popular stories, and their very different sources of authority.

In a journal article, the goal is to convince other experts. In other words, the article should ideally be self contained, assembling all the relevant details so that an independent observer can make up their own mind.

In contrast, a popular science story aims merely to describe the conclusions, not prove them. As David Ehrenstein, the editor at Physical Review Focus, once told me, the goal is to present a plausibility argument for the conclusions: to give enough context and explanation that readers can appreciate what's being claimed and who's claiming it.

The last point is also critical: by and large, popular writing gains its authority from the quoted judgments of experts, not directly from the model or observations. Indirectly, of course, this authority comes from the reputation of the writer and the publication (that is, the editors), because they are the ones who decide which commentators are worth quoting. (Of course, those commentators must also respond to emails or phone calls!)

Since the goal is plausibility and a qualitative understanding, the limited precision of ordinary writing is usually good enough to convey the message.

Survival of the Most Entangled

Most people think quantum-mechanics affects only atomic-sized objects, but many experiments have shown that it applies over many miles. In an experiment last year, for example, researchers sent pairs of light particles, or photons, between two of the Canary Islands off the coast of Africa, a distance of 144 kilometers.

http://www.flickr.com/photos/tenerife/ / CC BY 2.0

This picture dimly shows La Palma, where the photons started, as seen from Tenerife, where they were detected.

Although the Austrian team, led by Anton Zeilinger, only detected one in a million of the pairs they sent, they found that these pairs retained the critical property of entanglement. This means that results of measurements on the two particles are related in ways that can't be explained if each particle responds to the measurement independently: the pair acts like a single quantum-mechanical entity. Such pairs can be used to securely transmit information over long distances.

My latest story at Physical Review Focus describes a theoretical analysis of this experiment by researchers in Ukraine and Germany. They suggest that the pairs that survive the half-millisecond trip must have had unusually smooth sailing through the turbulent atmosphere, and that this is part of the reason why they are still entangled. (The motion of the air, like the shimmering of a mirage in the desert, generally disrupts the light transmission, but there are short moments of clarity.) This is a pretty comprehensible idea, so in the story I was able to sidestep a lot of interesting issues about how the entanglement was measured and what it means.

For example, the experimenters delayed one photon by about 50 ns by passing it through a fiber before sending it after the other one. That's not a long time, so the atmospheric conditions probably looked pretty similar to the two photons. Since they were subjected to much the same conditions, it doesn't seem so surprising that they would remain entangled. In fact, the original experimenters were pretty pleased that it all worked, but clearly they were hoping it might or they wouldn't have gone to the trouble.

Sending the two photons on the same path certainly isn't the most demanding task, either. More impressive would be sending them on different routes to a final destination where they were compared. But sending an entangled pair is good enough for some quantum communication schemes.

What made the paper particularly interesting was the conclusion that the turbulent atmosphere would be better than, say, an optical fiber that had the same average loss, because the fiber's properties wouldn't change with time. Zeilinger expressed pleasant surprise that the rare moments of exceptional clarity would more than make up for the times when the atmosphere was worse than usual. Still, having no turbulence at all (or a very clear fiber) would be even better.

Exploiting quantum mechanics in secure long-distance communication, for example via satellites, looks more realistic than ever.

Stoner Magnetism

My latest story at Physical Review Focus describes experimental evidence that a missing atom in a chicken-wire-like sheet of carbon can hold a single extra electron.

Theorists have long expected this to be the case, and that unpaired electrons on such vacancies might join up to make an entire single-atom-thick graphene sheet magnetic at relatively high temperatures. Many researchers are excited about the rapid and unusual motion of electrons in these sheets, and IBM researchers recently described a graphene field-effect transistor, grown on silicon carbide, whose expected frequency (f_T) exceeds 100GHz. If the layers are also magnetic at normal temperatures, this material could be fun and potentially practical for spintronics, which manipulates both the charge and magnetic properties of electrons.

The actually experiment didn't directly show magnetism, though, just a state that looked like it should hold only one electron. The researchers used scanning-tunneling microscopy to look at a clean, cold graphite surface, which includes many stacked graphene-like layers. In fact, the authors suggest that magnetism may exist in graphite, but not in graphene, because in the latter the effects of two equivalent carbon positions for a vacancy may cancel each other out.

It turns out to be a little bit tricky to explain the connection between local spins, which naturally carry a magnetic moment, and magnetism in a bulk material.

The usual story is straightforward: some types of atoms (or vacancies) naturally have a magnetic moment, "like a tiny bar magnet." Nearby moments exert forces that tend to align their neighbors, either the same way or oppositely. If it's the same, then the moments on many different atoms can all line up to form a net magnetization in a large sample, if the temperature is not so high that they get jostled out of position.

This description is correct--but only for some magnets.

For other magnets, it's just not accurate to say that the atoms each have magnetic moments that line up with each other. In these so-called "itinerant" magnets, the magnetization comes from the metallic electrons washing over all of the atoms. In this case, preference for one direction or another at a particular atom develops only as a part of the magnetization of the whole sample.

Mathematically, itinerant magnetism takes the form of an instability, in which the energy benefit of aligning the moments of the electrons overcomes the energy cost of doing so. A simple description was developed back in the 1940s by Edmund Stoner at the University of Leeds, and his name is still used to convey the ideas. (I apologize to anyone who expected this post to be about the natural charisma of pot-smokers.)

Of course, the distinction between the "local-moment" and "itinerant" magnetism is often somewhat fuzzy, and for the purpose of explanation to the general public it may not seem that important. But to people who understand the issues, getting it wrong is unforgivable, as I found out to my chagrin after using the above simple local picture in my Focus story on the 2007 Physics Nobel on Giant Magnetoresistance (GMR).

GMR read heads in disc drives can be seen as a simple type of spintronics device. In more sophisticated devices that people dream about, electrons will carry their magnetization to new locations, so it's important to be clear on the nature of that magnetism.

Brain-Machine Interfaces

I have a short news story about exchanging information between machines and people's brains, now online at the Communications of the Association for Computing Machinery. This is a difficult field to capture in a few hundred words. There's a lot of progress, but people are trying a lot of different approaches, and they're not all addressing the same problem.

For example, some people are hoping to provide much needed help to people with disabilities, while others see the opportunity for new user interfaces for games.

Naturally, people will be willing to spend a lot more for the rehabilitation. In addition, recreational use pretty much rules out (I hope!) any approach that requires surgically implanting something in the skull. Even the researchers who are exploring rehabilitation don't yet feel confident exposing people to the risk, because they can't be sure of any benefits. As a result, these studies mostly involve patients who have received implants for other reasons.

If surgery is ruled out, there are fairly few ways to get at what's going on in the brain. With huge, expensive machines, you can do functional MRI, but that doesn't look particularly practical. Both Honda and Hitachi are using infrared monitoring of blood flow, with impressive results. But the best established measurement is EEG, which measures electrical signals with electrodes pasted to the surface of the head.

One up-and-coming technique that I mention in the story is called ECoG, or electrocorticography. Like EEG, it measures the "field potentials" that result from the combined actions of many neurons. However, the electrodes are in an array that is draped over the surface of the brain (yes, under the skull), so the signal is much cleaner.

Finally there are approaches like Braingate that put an array of a few dozen electrodes right into the cortex, where they can monitor the spikes from individual neurons. 60 Minutes did a story a while ago that showed people using this technology to move a computer mouse.

If the implants are to be practical, they will need to be powered and interrogated remotely, not through a bundle of wires snaking through the skull. Many people are exploring wireless interfaces for this purpose, as described by my NYU classmate Prachi Patel in IEEE Spectrum.

Brain-machine interfaces can also run in either direction. My story dealt mostly with trying to tap the output of the brain, for example letting paralyzed people control a wheelchair or computer mouse. But input devices, such as artificial cochleas or retinas, are also proceeding quite rapidly. To my surprise, Rahul Sarpeshkar, who works on both directions, told me the issues are not that different.

My guess would have been that input to the brain can take advantage of the brain's natural plasticity, which will adapt it to a crude incoming signal. To usefully interpret the output of haphazardly placed electrodes, people need to do an awful lot of sophisticated processing of the signal, which can slow things down.

The toughest thing about this sort of story, though, is time. There's a lot of progress, but there's a long way to go. Once the proof of principle is in hand, there's still a lot of hard work to do, some of which may involve major decisions about basic aspects of the system. It's hard to communicate the progress that's being made without getting into a lot of details that are only interesting to specialists.

Even when it lets the blind see or the lame walk, writing about engineering is a hard sell for the general public.

Don't Fear the Hyphen

Hyphens come up a lot in scientific writing. Or at least they should. Unfortunately, small as they are, many people are afraid of them.

One problem is that hyphens get used for some very different purposes, although all of them tend to bind words or fragments together. I'm only going to talk here about making compound words with them.

Another problem is that you don't have to use a hyphen if you don't have to: if the meaning is clear without it (semantics), you're allowed to omit it (punctuation). This makes it very hard to figure out the real punctuation rules, since they don't arise from syntax alone.

Compound words are hard to predict. Sometimes two words are locked together to form one new word, as in German: eyewitness. Sometimes the two words keep their distance even as they form a single, new concept: eye shadow. But some pairs are bound with the medium-strength hyphen: eye-opener. This mostly happens when both words are nouns, so that the first noun is acting as an adjective, making the second more specialized.

There's really no perfect way to know which form is favored, and it varies over time. Novel pairings generally start out separated and become hyphenated when they seem to represent a unique combined identity. When that combined form becomes so familiar that it is easily recognized, the hyphen disappears, (unless the result would be confusing, as in a recent example, "muppethugging," or the less novel "cowriting.") You just have to look in an up-to-date dictionary.

For the single compound words and those that are always hyphenated that's the end of the story. The problem is that the isolated pairs of words sometimes should be hyphenated, too. This hyphenation is not a property of the pair, and it can't be found in the dictionary. It's a real punctuation mark, and depends on the details of the sentence.

The hyphen belongs when the pair is used as an adjective, known as a compound modifier, as in the previous "medium-strength hyphen." But generally the hyphen is omitted when the adjective occurs later on: "The hyphen has a medium strength." But the AP Stylebook (not hyphenated!) says that when that "after a form of to be, the hyphen usually must be retained to avoid confusion: The man is well-known." AP also has a rule that when for an adverb-adjective pair, the hyphen is not used if the adverb is "very" or ends in "-ly."

OK, this is getting confusing, so let's regroup: The important principle is that the hyphen is there to make clear when there is a link that might otherwise be missed. If we talk about a "highly important person," it's clear that it's the importance that's high, not the person. But if we talk about a "little known person," it's not so obvious whether it's the knowledge or the person that's diminutive, because
"little" can be an adjective or an adverb. If it's an adjective, you might have said "little, known person, " but "little-known person" avoids any chance of confusion.

The problem is worse when the first word is a noun, because it doesn't really give you any syntax clues about whether it's acting as an adjective or adverb. This issue comes up frequently in science writing. I imagine most people will realize that a "surface area calculation," refers to a calculation of surface area, and not a surface calculation of the area. But sometimes it's hard to know what will be confusing. I prefer to assume as little possible about what my readers are getting, so I would use "surface-area calculation." But many editors correct this (and I generally defer to them).

Unfortunately, there is a compelling to reason to be sparing with hyphens, which is that they can't be nested. This also comes up frequently in science writing, when a compound modifier is constructed from another compound modifier, as in "surface area calculation results." If we used parentheses to tie together related words, this would be rendered "((surface area) calculation) results." But there's no way to indicate priority with hyphens.

The right thing to do is to decide what level of compounding needs to be made explicit, and retain hyphens at all levels up to that, for example "surface-area-calculation results." Sadly, I frequently see something like "surface area-calculation results." That's just wrong, since the hyphen ties together "area" and "calculation" more strongly than "surface" and "area." In this case you'd be better off leaving out all hyphens and hoping for the best.

Of course, as in most cases of confusing writing, the best alternative is "none of the above": recast the sentence so that it doesn't have compound-compound modifiers. "The results of the surface-area calculation" leaves nothing to chance. But it's clunkier.

Monday Morning Quarterbacks

Many news stories simply report the facts; the better ones put the facts in the context and explore their likely impact.

Then there are stories that explain "why."

I have a simple assessment for these explanation stories that saves me a lot of time. This is it:

"What's new?"

More specifically, is there anything about the "explanation" that wasn't known before the event actually happened? If not, click on.

A classic example is election-night analysis. Even before all the votes are counted, pundits materialize to explain what message the voters were trying to send, and which campaign screwed up.

Unfortunately, most of what they say was just as true the day before. Sure, they now have more precise results, and maybe a geographic breakdown and some exit polls. But most of the commentators' facts were already known to everyone. Somehow the surrounding story seems more profound once it aligns with actual events--and once the arguments for the other side have been conveniently forgotten.

Stories about stocks can also be amusing, or pathetic. It's hard to find any report on a market move that doesn't attribute it to concern about Chinese exports, or some such. When the market is truly uncooperative, analysts resort to saying that it "shrugged off" some really dire economic news. Sorry, guys. If you knew how the market would react, you'd be rich.

Unfortunately, the challenge of explanation applies to the real economy as well. I'm a regular reader of Paul Krugman, who warned a year ago that the stimulus package would likely not generate enough jobs. Sure enough, we now have an unemployment rate that once would have been thought unacceptable. So was Krugman right? Or were the conservatives who said the stimulus just wouldn't work?

The sad fact is we hardly know any better now than we did a year ago. We know what happened, of course. But we still don't know what would have happened if we had done something different. Evaluating such past hypothetical situations requires the same kind of modeling, and relies on the same ideological assumptions, as predictions do. Unsurprisingly, the experts mostly see the past the same way they saw the future.

The same problem may apply to climate change. I don't usually think of the existence of global warming as a political question (as opposed the policy response). In a hundred years, after all, liberals and conservatives will both suffer the same heat and drought and see the same sea level rise, or not. But even then, they probably won't agree on what we did, or didn't do, to get them there. We don't have a duplicate world to do control experiments on.

As Yogi Berra is quoted, "Predictions are hard, especially about the future." Sadly, they are almost as hard about the past.

Sys Devo

Lawrence Berkeley Labs

My latest eBriefing for the New York Academy of Sciences, Growth Networks: Systems Biology Meets Developmental Biology, is now up (the direct link should work only for Academy members; others may get to it through the NYAS page of my website.)

The symposium was very interesting, but, as often happens, it was challenging to present the three talks as a coherent unit. In this case, the overall message (provided by the visionary organizer, Andrea Califano) is that the sweeping and irreversible changes that occur during early development, which are often driven by a relatively few molecular events (perhaps dozens), can provide stringent and useful tests for understanding molecular regulation. This is quite a different way to learn about networks than by gently poking ("perturbing," for example with stress or drugs or RNA interference) a mature animal, in which various molecules are generally cooperating to keep things stable.

The hope is that the overlap between development and systems biology, can have the sort of powerful synergy that have enriched evolutionary and developmental biology in Evo Devo, as popularized by Sean B. Carroll and others. But I suspect the final synthesis will be more of a three way combination, SysEvoDevo.

Angela DePace of Harvard, for example, described her nascent efforts to exploit evolutionary comparisons between related species from the fly genus Drosophila, which have been a playground for development (once called embryology) for nearly a century. In the past couple of decades researchers have learned how to modify particular genes so they produce fluorescent molecules of various colors along with their normal protein products. The results have shown in living color how various transcription factors interact to generate that spatial patterns and compartments that ultimately shape the segmented body of the fly. DePace and her former colleagues at Lawrence Berkeley Labs refined the technique to let them measure the quantitative changes in gene expression at thousands of individual cells in the early embryo (see the figure), which let them test the models of gene activity (and the differences between species) in fascinating detail.

Stanislav Shvartsman of Princeton also looked at early Drosophila development, but he showed that the transcription factors alone don't explain everything. Instead, some of the patterning depends on protein phosphorylation, which is a half-century old process that among other things carries signals from a cell's outer membrane to its nucleus, but is rarely considered in development. Antonio Iavarone of Columbia studies the development of the early nervous system in mice from stem cells to differentiated neurons. This is a process that is subverted by brain cancers, which re-activate this cellular program to grow and nourish themselves.

Pulling these three diverse talks together was a bit of a shoe-horning exercise, but they were all fascinating.

Rules or Consequences

Can we learn about one phenomenon by studying a completely different one?

Putative "laboratory versions" of exotic phenomena appear regularly in the news, such as microwave analogs of "rogue" ocean waves, optical-fiber analogs of rogue waves and black holes, and, as I've discussed here, magnetic-crystal analogs of magnetic monopoles.

But not all of these experiments are equally illuminating. Researchers, and journalists who write about them, need to think clearly about how the two systems are related, and what's missing. Experiments on a model system can show what behavior arises from shared underlying rules, and how that behavior changes as conditions change. But only experiments on the original system can test whether those rules are relevant.

The results of known mathematical rules aren't always obvious. Even Newton's second law, which relates the force on an object to its acceleration, only stipulates a differential equation that researchers must solve to find how an objects position changes with time. When the force is constant, this is easy: the position follows a parabolic course in time.

For more complicated situations, scientists often can't relate the rules to the end result. In some cases they turn to simulations, which can be regarded as a model system that, ideally, embodies the mathematical rules perfectly. But simulations are often restricted to unrealistically small systems that could behave differently than the real McCoy.

In these cases, researchers can learn from actual systems that--they think--follow similar rules. For one thing, this may make precision measurements easier. Placing a block on an inclined plane, for example, slows down its acceleration due to gravity, making it possible to test the parabolic law more precisely.

Unfortunately, the model system may introduce complications of its own. The friction on a sliding block is significantly different than that air friction on a falling body--for example it's much larger before the block starts to move. Even though the rules of gravitational force are the same, the differences may completely obscure the relationship between the two systems. Researchers must then spend a lot of energy tracking down these differences.

But to draw any parallel between two systems, researchers must establish that both are governed by similar rules. Unless they know that, seeing a particular behavior in a model system, by itself, is irrelevant for deciding if the original system follows the same rules. The way to test that--but not prove it--is to do experiments on that system, and see if the behavior is similar.

In our example, if an object follows a parabolic time course, it might well be that it is responding to a constant force. (Of course, it may just be moving through curved spacetime.) With luck, the model system--the inclined plane--would have demonstrated something close to this parabolic result, even if the equations had been unsolvable. The model system then hints at a similarity of the governing rules.

Similarly, a chaotic microwave cavity or an optical fiber might show a "long tail" in the distribution of wave heights that mathematically resembles that which is experimentally measured on the ocean, and which occasionally spawns mammoth rogue waves. Because it's easier to vary the conditions in the laboratory, these experiments might also show what aspects of wave propagation are relevant to rogue-wave formation. In these systems, researchers already understand the basic features of wave propagation--the question is what happens when they combine the ingredients in various ways.

In contrast, physicists do not know whether the basic equations of physics allow magnetic monopoles. Some grand unified theories predict them, but they've never been seen in free space, despite extensive experiments. The observation of monopole excitations at low temperatures in magnetic materials called spin ices has absolutely no implications for the nature of the fundamental equations. It may be that it helps to understand how "real" monopoles would behave, if they exist. But it says nothing about whether they do.

Model systems can reveal important relationships between models and behavior. They can also uncover real-world complications that need to be included to make models more relevant. But to find out whether a model applies to a particular system in the first place, researchers need experiments on that system. Experiments on a model system aren't enough.

 

 

New Guidelines for Breast-Cancer Screening

A few weeks ago, as I reported here, Gina Kolata at the New York Times reported that the American Cancer Society was planning to scale back their recommendations on routine screening for prostate and breast cancers.

As discussed by the Knight Tracker, she got a lot of grief for this story, and the next day the Times published a more reserved follow-up story by Tara Parker-Pope, also discussed by the Tracker. In fact, her primary source at the society, Dr. Otis Brawley, later wrote a letter to the editor denying any intention to change the guidelines (although he is on record cautioning about overscreening).

This isn't the first time that a page-one story by Kolata has gotten into trouble. Her 1998 story on cancer drugs was cited as a cautionary tale in my medical-writing course at NYU. That story quoted James Watson as saying (privately, at a banquet) that Judah Folkman was "going to cure cancer in two years" with his amniogenesis inhibitors. Watson later denied saying any such thing.

Nonetheless, Kolata accurately conveyed a painful dilemma of cancer screening: more isn't necessarily better. Not for all cancers, and not for all patients.

The U.S Preventive Services Task Force has now issued revised recommendations for breast-cancer screening for patients who have no indications of high risk. In part, they moved the earliest age for mammography back up from 40 to 50, at which point they recommend a scan every two years rather than every year.

These recommendations were based not primarily on financial costs, but on health risks to patients:

"The harms resulting from screening for breast cancer include psychological harms, unnecessary imaging tests and biopsies in women without cancer, and inconvenience due to false-positive screening results. Furthermore, one must also consider the harms associated with treatment of cancer that would not become clinically apparent during a woman's lifetime (overdiagnosis), as well as the harms of unnecessary earlier treatment of breast cancer that would have become clinically apparent but would not have shortened a woman's life. Radiation exposure (from radiologic tests), although a minor concern, is also a consideration."

The blog, Science-Based Medicine, has a thoughtful and thorough discussion of the issue, written before the recent recommendations. I highly recommend it.

In a rather odd move, the Times published a balancing article by Roni Caryn Rabin on the same day (at least in the paper edition), although it was buried in the "Health" section, not on the front page with Kolata's.

Rabin's story empathetically interviews screening advocates, including people who have been treated for breast cancer. But in its empathy, story misses the opportunity to clarify the issues. Or perhaps in the extended quotes, the author is deliberately allowing the sources to reveal themselves? It's hard to tell.

For example, one woman calls screening her "security blanket." "'If someone ran a computer analysis that determined that wearing a seat belt is not going to protect you from being killed during a crash, would you stop using a seat belt?' Ms. Young-Levi asked."

Although it's hard to imagine, I certainly would stop using a seat belt if the best evidence indicated it, whatever psychological security I might ascribe to it.

The story later quotes another survivor: "'You're going to start losing a lot of women,' said Sylvia Moritz, 54, of Manhattan, who learned she had breast cancer at 48 after an annual mammogram. 'I have two friends in their 40s who were just diagnosed with breast cancer. One of them just turned 41. If they had waited until she was 50 to do a routine mammogram, they wouldn't have to bother on her part — she'd be dead.'"

The author negligently lets this quote stand: the whole point of the recommendations is that if those friends had not been diagnosed, they might be doing just fine now, without the risk of the tests and procedures they underwent because of the diagnosis.

But the unfortunate reality is that we need tests that better predict cancer progression, rather than merely signaling its presence. Without such tests, the recommendations can only trade off lives lost (and other damage) because treatment was unnecessarily aggressive with other lives lost because it wasn't aggressive enough.

Kansas City Here I Come

I'm going to Kansas City.

I've been invited to give a talk Tuesday at the Stowers Institute for Medical Research, based on my story this summer in Science about the surprisingly weak connection between the apparent biological importance of a DNA sequence and the preservation of it sequence through evolution.

I thought at first that Stowers had mistaken me for a real researcher. But they assured me that a writer can sometimes do a better job of providing perspective than a research who is immersed in day-to-day technical details. Since hosting Matt Ridley in 2001, the Institute has periodically included science writers among their speakers.

Preparing the slides for the talk has been a lot of work, but it has reminded me of some big differences between communicating science as a spectator and as a participant.

The most obvious difference is the thoroughness of the discussion. For one researcher to convince another requires data, covering the entire logical chain as well as possible alternative explanations. In contrast, a journalist rarely gives a complete description of the evidence. Instead, as David Ehrenstein, the Physical Review Focus editor, likes to say, we are happy to convince the reader of the plausibility of a conclusion.

This breezier discussion of the evidence gives journalists a freedom to convey the big picture. Ordinary researchers rarely get this opportunity, until their reputations reach a level where others are happy to hear their opinions for their own sake. This freedom is a terrific luxury for science writers.

Ideally, however, a journalist is not expressing a single opinion, however wise, but synthesizing or contrasting the range of opinions in a field. When this is done well, it conveys the entirety of a field more accurately than any single view. Unfortunately, in active, contentious fields, it's easy to get bogged down in the disagreements, obscuring instead of illuminating the big picture. The common journalistic focus on conflict doesn't help.

Especially when covering disagreements, the journalist needs to convey a sense of authority about the key issues are, if not their ultimate resolution. Without being able to rely on the detailed technical results, this authority often comes from the researchers ("sources") interviewed for the story. Of course, a well-written story can suggest authority even when these sources are not representative of the field, which is one reasons science writers are not created equal.

To convey this authority, journalists often use direct quotes. Again, the reader is dependent on the writer to choose truly representative quotes from a much longer interview with each scientist. Still, this appeal to authority (other than the speaker's) rarely happens in scientific presentations.

Finally, the nature of visuals is strikingly different in technical talks and science writing. In a talk, a scientist might use a cartoon or other light material as a diversion, but the meat will be data: descriptions of procedures, photographs of representative results, graphs summarizing the results, and perhaps an abstract representation or cartoon to convey the concept. In a journal article, in fact, many researchers reading a journal article will skip the text and go straight to the figures.

For much science writing, the only one of these elements that is at all likely to survive is the cartoon conveying the concept. The supporting details get short shrift. For many outlets, the figures won't have any meat at all, and may have only a tangential relation to the subject. As a result, the heavy lifting for science journalism is all done by the written word. Clearly this approach does not translate to a presentation, unless it is a classic speech without visuals.

The PowerPoint presentation I'll be presenting at the Stowers Institute will be a kind of mutant hybrid. I don't plan to use any direct quotes on the slides, for example. But I expect I'll do some name dropping and invoke my interviews for authority, especially to convince the audience that there is a puzzle to be solved in the relationship between evolutionary constraint and biological function. Hopefully I'll be able to get that bigger puzzle across, as well as the intriguing possibilities that may arise by solving it.

As Isaac Asimov said, "the most exciting phrase to hear in science, the one that heralds new discoveries, is not 'Eureka!' (I've found it!), but 'That's funny....'"

 

Junk or No Junk?

The phrase "junk DNA" is a hot button. Authors of press releases, news stories, and even some journal articles seem powerless to resist casting any new discovery of function in non-protein-coding DNA as overthrowing a cherished belief that most of the DNA is junk.

In contrast, bloggers including T. Ryan Gregory and Larry Moran regularly gripe that this framing, like many "people used to think x, but now…" stories, is misleading: biologists have known for decades that non-coding DNA contains important regulatory and other functional sequences. Nobody seriously thought it was all junk: that's just a myth that makes the story seem more exciting.

Still, most biologists agree that DNA is mostly junk.

John Mattick is not so sure.

In a 2007 paper in Genome Research, Mattick and his co-author Michael Pheasant, both of the University of Queensland in Australia, suggested that evolution could be sheltering much more than the 5% of the genome estimated by the ENCODE project and others. Those researchers estimate the background rate of neutral evolution by looking at sequences that they assume to be useless, such as "ancient repeats" left behind from long-ago genomic invasions.

Instead, if these sequences are a little bit useful, perhaps because they are occasionally drafted by the cell for other uses, then they would be slightly preserved during evolution. If this is the case, then other sequences that are also slightly preserved may be useful, too.

I discussed this issue with Mattick for my story for Science (subscribers only), but it was hard enough to capture the issues for strongly selected sequences, so this subject didn't make the cut. Mattick didn't claim that the issue is settled, only that the logic was in danger of being circular: "It is basically an open question. We have no good idea how much of the genome is conserved, except for that which is dependent on questionable assumptions about the nonconservation of reference sequence."

For him, the extensive transcription of the genome seen by ENCODE may not be a sign that RNA production is unselective, but that a large fraction of the DNA is serving some useful, if so far unknown, function.

Mattick described himself as a "minor author" among the scores on the ENCODE project. Ewan Birney, of the European Bioinformatics Institute in the U.K., played a coordinating role. But he doesn't strongly dispute Mattick's observations. "Ancient repeats provide a marker of evolution. They may very well be under some selection," Birney said. But "the striking thing," he stressed, "regardless about where the line is between selection and no selection, is that a lot of the functional regions are at the absolute lowest end of what we see across the human genome." They may be important, but not very important.

Or maybe the biochemical assays don't measure biological importance at all. "Many people instinctively feel," Birney said, "that all the functional elements really must be selected for in some sense. But there's alternative view, which is that there's just a big set of cases which are generated randomly, are perfectly assayable, when you assay them they're always there in that species, but in fact evolution doesn't select either for or against them. They are truly neutral elements: they are selected neither for nor against."

More philosophically, Birney doesn't find the evolutionary question to be central to short-term concerns about human health. "For disease biology we're interested in understanding the disease. We're not so interested in proving whether they're weakly under selection or something like that."

In fact, for both Birney and Mattick, the extensive biochemical activity of the weakly selected 95% of the DNA suggests its potential as a reservoir of "spare parts." Whether or not the long-term potential of that reservoir puts evolutionary pressure on its components, so that they are conserved, may not be the key issue. The important thing is that those partially-assembled genetic tools are ready to be called into action for future innovations.

 

 

Climate Cover-Up

In their new book, Climate Cover-Up: The Crusade to Deny Global Warming, James Hoggan and Richard Littlemore waste little time wringing their hands about the reality or seriousness of the global warming threat. They dispense with this question quickly, showing that the essential features of carbon-dioxide induce warming have been known for over a century.

Although a devil might lurk in the details, the recent state of the science is captured by Naomi Oreskes' 2004 literature study in Science, which found zero dissenters from the consensus among 928 journal articles referencing "global climate change." Similarly, the 2007 Fourth Report of the Intergovernmental Panel on Climate Change, whose political charter leads it to avoid poorly understood possibilities like collapsing ice sheets, nonetheless states that "most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic [greenhouse gas] concentrations."

In contrast, a Pew Survey released last week concludes that only 36% of Americans think there is solid evidence that the Earth is warming because of human activity, down from an already low 47% over the past few years. Climate Cover-Up explores how it has come to pass that the public still thinks that this is an open scientific question. Hoggan and Littlemore describe the extensive, organized efforts to make it appear open, largely funded by corporations with much to lose from effective climate actions.

Hoggan is a public-relations professional who says that PR people have a duty to serve the public good. In 2005 he founded DeSmogBlog to highlight just the sorts of systematic distortions that the book catalogs, and Littlemore is editor at the site. Their highly readable book describes these efforts, and the funding behind them, with journalistic precision and documentation.

Their laundry list of deception includes "astroturf" groups that use sanitized corporate funds to present a "grass roots" appearance; "think tanks" that increasingly eschew analysis for promotion of policies that favor their sponsors, and petitions signed by scientists who are not or who have little or no expertise in climate. Hoggan and Littlemore systematically discuss these and other programs to frame the "debate" as one in which huge uncertainties remain--as if that should be a source of comfort.

Sowing doubt is a tried-and-true strategy for delaying government response. David Michaels' excellent 2008 book, Doubt Is Their Product, for example, and Devra Davis' 2007 The Secret War on Cancer related how the tobacco industry perfected this technique to delay serious government action against their product for decades. Some of the same firms are coordinating the skeptical response to climate change, and some of the same scientists, like Frederick Seitz and S. Fred Singer, have played roles in both controversies (despite having expertise in neither cancer nor climate).

Hoggan and Littlemore describe how these omnipresent figures benefit financially from their support of corporate needs, and they reveal the irrelevance of many of the "thousands" of signatories on some highly publicized petitions. But they don't address why other scientists--many intelligent and sincere--sign on to such statements. Why are researchers who have no expertise in climate, as well as members of the public, so willing to question those who do, when they would never presume to second guess articles about cancer treatments or particle theory?

In the end, though, these efforts have achieved their goal: keeping the journalistic treatment of global warming "balanced," unlike the clear trend in expert opinion. This problem was captured in a 2004 study by Maxwell T. Boykoff and Jules M. Boykoff, "Balance as bias: global warming and the US prestige press" which was published in 2004 in the journal Global Environmental Change, and in Chris Mooney's story, "Blinded by science: how 'balanced' coverage lets the scientific fringe hijack reality" in Columbia Journalism Review later that year.

This book is not likely to convince true skeptics of the seriousness of global warming. For those who understand the stakes, however, the book is a powerful inoculation to help recognize the conspiracy-theory talking points, most recently regurgitated by the authors of SuperFreakonomics, for the misinformation it is.

Where there's smoke, there's not always fire. Sometimes, it's a massive corporate-sponsored campaign to blow smoke.

Freedom (From Cancer) Is Not Free

For decades, the American Cancer Society has been a stalwart advocate of steps to reduce cancer risk, including early testing. In a fine story in today's New York Times (registration required), Gina Kolata reports that they are about to back off on those guidelines, for breast and prostate cancers.

The essential issue is that early screening can find small tumors that might never become a problem, or might even disappear on their own. For these tumors, biopsies, further tests, or treatments are an unnecessary financial burden and also a health risk. On the other hand, many rapidly growing tumors may become serious problems in the time between tests.

In a related article (subscription required) published tomorrow [sic] in the Journal of the American Medical Association, entitled "Rethinking Screening for Breast Cancer and Prostate Cancer," three doctors review the disappointing results of twenty years of early detection, and conclude:

"One possible explanation is that screening may be increasing the burden of low-risk cancers without significantly reducing the burden of more aggressively growing cancers and therefore not resulting in the anticipated reduction in cancer mortality."

These results underline the need for measuring the comparative effectiveness of all medical procedures. Not everything that seems like a good idea really is. For every patient whose aggressive early cancer is stopped in its tracks (and whose doctors will vividly remember the events), there are others for whom the trauma, health risk, and expense were unnecessary--and avoidable.

In his book, The Healing of America (which I reviewed here), T.R. Reid notes that the PSA (prostate-specific antigen) test that is routinely given to older men in the U.S. is not paid for by the Public Health Service in the U.K. (p. 120). No doubt this is partially a matter of cost effectiveness. But as his British doctor explained, it is also a matter of medical effectiveness. It may seem brutal to trade off the few lives saved by early testing with lives lost by unnecessary intervention, but such statistical comparisons are, for now, our only option.

Ultimately, though, we need better tests: tests that can identify the molecular or other markers that distinguish between aggressive tumors that people will die from and more passive cancers that people will die with. As the JAMA authors conclude, "To reduce morbidity and mortality from prostate cancer
and breast cancer, new approaches for screening, early detection,
and prevention for both diseases should be considered."

[Update: Paul Raeburn at the Knight Science Journalism Tracker notes that although other outlets covered this issue, Kolata is unique in projecting a revision from the American Chemical Society.]

[Update (11/7/09): Science-Based Medicine has a fantastic, detailed discussion of the science behind this issue. Short message: keep screening.]

Blogstorm Warning: SuperFreakonomics

Is all publicity good publicity? Stephen Dubner and Steven Levitt, the authors of the bestselling book Freakonomics and the like-named blog, may find out. I, for one, have shelved any inclination to buy their new book, SuperFreakonomics: Global Cooling, Patriotic Prostitutes, and Why Suicide Bombers Should Buy Life Insurance, after seeing the blogosphere's reaction to its climate-change chapter.

The battle was joined in this post by the vocal climate-change activist (and fellow MIT physics PhD) Joe Romm. Romm followed up here, here, here, and here, giving some credence to the idea that he has an axe to grind. But in light of the wide audience the book is likely to get, a preemptive takedown might be justified.

Among Romm's claims is that the Steves misrepresent the views of Ken Caldeira, the Stanford ecologist who has been promoting research into geoengineering approaches to global warming. Romm quotes the book as saying of Caldeira, "his research tells him that carbon dioxide is not the right villain in this fight." Meanwhile, Caldeira's web page prominently features this statement: "Carbon dioxide is the right villain," says Caldeira, "insofar as inanimate objects can be villains." Sounds pretty clear.

Romm may not be entirely clean, though. Dubner claims that Romm goaded Caldeira into disavowing the book's characterization. Roger Pielke Jr., who has had his own battles with Romm, regards him as a liar. It does look as though Romm may have compromised his credibility, although his latest post makes a good defense.

But even if Romm made mistakes, it doesn't make those in SuperFreakonomics any more excusable. It is simply disingenuous to claim, as Dubner does, that the "Global Cooling" in the subtitle is supposed to refer to geoengineering solutions, not to the canard that there was a scientific consensus in the 1970s that climate was in danger of cooling. As painstakingly tabulated by Brad DeLong, this is just one of a whole host of misleading or mistaken statements in the book. Paul Krugman also takes issue with the Steves' take on a particular economics case for early action.

Krugman sums up the problem with Freakonomics' trademark contrarianism:

Clever snark like this can get you a long way in career terms — but the trick is knowing when to stop. It's one thing to do this on relatively inconsequential media or cultural issues. But if you're going to get into issues that are both important and the subject of serious study, like the fate of the planet, you'd better be very careful not to stray over the line between being counterintuitive and being just plain, unforgivably wrong.

What's In a Name?

I was surprised to see a fresh flurry of news stories in the last few days, more than a month and a half after two papers about ostensible magnetic monopoles in spin ices were posted online (although they just came out in print.)

I want to say one word to you. Just one word.

Are you listening?

Magnetricity.

Apparently one of the teams behind the monopole experiments has a new letter to Nature (with an accompanying News and Views article) measuring the total magnetic "charge" in a model-independent way using muons. (See the lifted graphic for a little explanation.)

The researchers adapted a venerable technique for measuring the charges of ions in electrolyte solutions. In a magnetic field, opposite monopoles drift in opposite directions, and the muons sense the field that results from their separation. Seems like a nice experiment.

But by calling the effect "magnetricity," the scientists insured themselves breathless coverage. It's great marketing, although as far as I can tell they did not measure the magnetic analog of an electric current as claimed by some news stories. They measured the separation that results from the current, but not the current itself.

According to the news release,

Dr Sean Giblin, instrument scientist at ISIS and co-author of the paper, added: "The results were astounding, using muons at ISIS we are finally able to confirm that magnetic charge really is conducted through certain materials at certain temperatures – just like the way ions conduct electricity in water."

Now you might not think that the lethargic drifting of magnetic "charges" that only exist in a very special crystal would form the basis of a new information technology, especially when you realize that "certain temperatures" are about a degree above absolute zero. After all, drifting electric charges in electrolytes (like batteries) are only important because they liberate truly mobile electrons in attached wires that do the real work.

But for researchers who only last month claimed to discover a fundamental particle predicted by Dirac, is revolutionizing electronics too much to ask? According to New Scientist,

Bramwell speculates that monopoles could one day be used as a much more compact form of memory than anything available today, given that the monopoles are only about the size of an atom.

"It is in the early stages, but who knows what the applications of magnetricity could be in 100 years time," he says.

I think I might be able to guess.

[Other stories at Physics World(the best one I saw), The Times, BBC, (did I mention the researchers were from the U.K.?), Popular Science, and Next Big Future.]

Science/Journalism

I've gotten many good insights from Chris Mooney. In a 2004 story in the Columbia Journalism Review called Blinded by Science, for example (oddly unlinkableposted here), he criticized the journalistic tradition of "balance," as it applied to climate change. He explained that although including diverse points of view gives an impression of objectivity, this habit was giving undeserved credibility to the rare deniers of the consensus on climate. In the intervening years, journalists have become more aware of this problem and more frank in distinguishing the mainstream from the fringe (supported by the increasingly dire predictions of the mainstream view).

In one small section of their recent book, Unscientific America: How Scientific Illiteracy Threatens Our Future, Chris and his coblogger at The Intersection, Sheril Kirshenbaum, expand on this and other ways that journalistic traditions obscure scientific realities. Chief among the disconnects is the news focus on, well, news: what's happening now that we didn't know yesterday? Such event-driven coverage serves poorly many ongoing trends in science (as well as in other areas) that develop continuously or incrementally. The need for a "hook" drives reporters to focus on specific articles in the big journals, rather than the accumulating evidence that they are merely an example of.

Journalists are also prone to framing stories around human elements, especially conflict. There are good reasons for this: people read these stories. But the focus on personalities or revolutions often distracts from the real issues. Biobloggers Larry Moran and T. Ryan Gregory, for example, routinely complain about the misleading narrative that "scientists used to think most of the genome was 'junk," but now they've realized it's good for something." (Scientists have long known that much of it was good for something. Much of it is still junk.)

These differences--driven largely by the business of journalism--are important. Scientists who can't follow Mooney and Kirshenbaum's dictum to transform into public communicators would do well to appreciate what happens to their message when it leaves their hands.

Nonetheless, as someone who has morphed from one to the other, I think the similarities between scientists and journalists are greater than the differences. At a fundamental level, both are professionals dedicated to uncovering reality, wherever it lies. Both groups rely on evidence, and treat personal opinions and popular fads with suspicion, as much as they can recognize them. In each profession, there is a strong social obligation that transcends any loyalty to one's employer or even to one's own prejudices. It is an obligation, as best one can, to speak the truth.

Forbidden Questions

To navigate the quantum world, you have to know what questions not to ask.

In the everyday world, we get along fine assuming that a baseball, for example, had a certain momentum even before we whacked it and felt the effects. But at the quantum level, an observable effect like the push on a bat does not give us permission to regard the ball's earlier momentum as having been a "real" quantity, independent of the swinging bat. Talking about such unobserved properties is a recipe for trouble.

This takes a lot of getting used to.

I ran head on into this problem in my latest story for Physical Review Focus. I first titled the story "How Long is a Photon?" and described the experiments as measuring the "duration of individual photons." That description was wrong, and came from asking forbidden questions.

Optics experts often measure the duration of pulses that are only a few femtoseconds (10^-15 seconds) long. This is much too fast for direct electronic measurements, so they do it by making two similar pulses and measuring whether they overlap. Delaying one of the pulses by more than their length stops them from overlapping. Actually the researchers repeat the experiment with millions of pairs of pulses, each with a particular delay, to build up a picture of how the overlap varies with delay. For pulses consisting of many photons, it is natural to regard the overlap time as reflecting the length of the underlying pulses.

The new experiments look a lot like this. But the difference is critical.

Kevin O'Donnell, at CICESE in Baja California, built on earlier experiments from the Weizmann Institute in Israel. Instead of pairs of pulses, however, these groups measure pairs of photons. They get the pairs by shining a steady green laser into a special crystal, which splits about one green photon in ten million into two infrared photons. Because these two photons are created as a pair in a single quantum-mechanical process, they are "entangled": properties deduced from measurements on one will always be related to properties deduced from measurements on the other, even if the measurements are done far apart.

The nature of this connection is one of the central oddities of quantum mechanics. In fact, we could save a lot of trouble by not talking about the individual photons at all, because in a profound sense they do not exist as separate entities, even after "they" move away from each other. But our language makes it hard to talk about a pair without think of it as a pair of something.

As in the experiments on pulses, O'Donnell delays one photon with respect to the other and measures their overlap. (I can say that without saying photon, but it gets a lot more complicated.) But as he explained to me, it is not meaningful to relate this overlap to the "length" of the photons. Instead, the result of the overlap experiment at different delays is a property of the combined state of the two photons. The final story, "The Overlap of Two Photons," takes pains to describe that correctly, at the cost of clunkier language and probably losing some readers.

As another example, a researcher who measures the energy of one photon in a pair can be assured that the energy of the other will be just right, so that their combined energy equals that of the original green photon. But that doesn't mean that the photon "had" that energy before the measurement was made. More complex experiments, in fact, show that the unmolested photon does not have any particular energy.

In the current experiment, you don't go too far wrong by imagining (incorrectly) that it measures the length of a photon. But this "bad habit," as described by David Mermin in Physics Today (subscribers only, or you can google the title), of conferring reality on properties that aren't or can't be measured, is the root of much confusion. More importantly, thinking (and talking) precisely about what actually exists is key to understanding the nature of the quantum world we inhabit.