Knocking on Heaven's Door (42 page)

BOOK: Knocking on Heaven's Door
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The Higgs mechanism, which is responsible for elementary particle masses, is an excellent example. As will be explained in the following chapter, the Higgs mechanism very eloquently explains how the symmetries associated with the weak force can be slightly broken. We haven’t yet discovered the Higgs boson—the particle that would provide incontrovertible evidence that the idea is correct. But the theory is so beautiful and so uniquely satisfies criteria required by both experiments and theory that most physicists believe it is realized in nature.

Simplicity is another important subjective criterion for theoretical physicists. We have a deep-rooted belief that simple elements underlie the complicated phenomena we see. Such a search for simple basic elements of which all reality is composed or resembles began long ago. In ancient Greece, Plato imagined perfect forms—geometric shapes and ideal beings that objects on Earth only approximate. Aristotle, too, believed in ideal forms, but in his case, he thought that the ideals that physical objects approximate would be revealed only through observations. Religions also often postulate a more perfect or more unified state that is removed from, but somehow connected to, reality. Even the story of the fall from the Garden of Eden presupposes an idealized prior world. Although the questions and methods of modern physics are very different from those of our ancestors, many physicists, too, are seeking a simpler universe—not in philosophy or religion, but in the fundamental ingredients that constitute our world.

The search for underlying scientific truth often involves looking for simple elements from which we can construct the complex and rich phenomena we observe. Such research often involves trying to identify meaningful patterns or organizing principles. Only with a concise realization of simple and elegant ideas do most scientists expect a proposal to have the potential to be right. A starting point involving the fewest inputs has the further benefit that it promises the most predictive power. When particle physicists consider suggestions for what might lie at the heart of the Standard Model, we usually become skeptical when the realization of an idea becomes too cumbersome.

Again, as with art, physical theories can be simple in themselves, or they may be complex compositions made up of simple and predictable elements. The end point of course isn’t necessarily simple, even when the initial components—and perhaps even the rules themselves—are.

The most extreme version of such pursuits is the search for a unifying theory consisting of only a few simple elements obeying a small set of rules. This quest is an ambitious—some might say an audacious—task. Clearly an obvious impediment prevents us from readily finding an elegant theory that completely accounts for all observations: the world around us manifests only a fraction of the simplicity that such a theory should embody. A unified theory, while being simple and elegant, must somehow accommodate enough structure to match observations. We would like to believe in a single simple, elegant, and predictable theory that underlies all of physics. Yet the universe is not as pure, simple, and ordered as the theories. Even with an underlying unified description, a lot of research will be necessary to connect it to the fascinating and complex phenomena we see in our world.

Of course, we can go too far in these characterizations of beauty or simplicity. A standard joke among students in our science or math classes involves professors who repeatedly refer to well-understood phenomena as “trivial,” no matter how complex they might be. The professor already knows the answer and the underlying elements and logic very well, but this is not so true for the students sitting in class. In retrospect, after they have reduced the problem to simple pieces, it can become trivial to them, too. But they first have to discover how to do that.

MODEL BUILDING

In the end, just as in life, science doesn’t have just a single criterion for beauty. We merely have some intuitions—along with experimental constraints—that we use to guide our search for knowledge. Beauty—both in art and science—might have some objective aspects, but almost any application involves taste and subjectivity.

For scientists, however, there is one big difference. Ultimately experiments will decide which, if any, of our ideas are correct. Scientific advances might exploit aesthetic criteria, but true scientific progress also requires understanding, predicting, and analyzing data. No matter how beautiful a theory appears, it can still be wrong, in which case it must be thrown away. Even the most intellectually satisfying theory has to be abandoned if it doesn’t work in the real world.

Nonetheless, before we reach the higher energies or distant parameters needed to determine the correct physical descriptions, physicists have no choice but to employ aesthetic and theoretical considerations to guess what lies beyond the Standard Model. In this interim, with only limited data, we rely on existing puzzles coupled with taste and organizational criteria to point the way forward.

Ideally, we’d like to be able to work through the consequences of a variety of possibilities.
Model building
is the name of the approach we use to do this. My colleagues and I explore various particle physics models, which are guesses for physical theories that might underlie the Standard Model. Our goals are simple principles that organize the complicated phenomena that appear on more readily visible scales so that we can resolve current puzzles in our understanding.

Physics model builders take the effective theory viewpoint and the desire to understand smaller and smaller distance scales very much to heart. We follow a “bottom-up” approach that starts with what we know—both the phenomena we can explain and those we find puzzling—and attempt to deduce the underlying model that explains the connections among observed elementary particle properties and their interactions.

The term “model” might evoke a physical structure such as a small-scale version of a building used to display and explore its architecture. Or you might think of numerical simulations on a computer that calculate the consequences of known physical principles—such as climate modeling or models for the spread of contagious diseases.

Modeling in particle physics is very different from either of these definitions. Particle models do, however, share some of the flair of models in magazines or fashion shows. Models, both on runways and in physics, illustrate imaginative new ideas. And people initially flock toward the beautiful ones—or at least those that are more striking or surprising. But in the end, they are drawn toward the ones that show true promise.

Needless to say, the similarities end there.

Particle physics models are guesses for what might underlie the theories whose predictions have been already tested and that we understand. Aesthetic criteria are important in deciding which ideas are worth pursuing. But so are consistency and testability of the ideas. Models characterize different underlying physical ingredients and principles that apply at distances and sizes that are smaller than those which have yet been experimentally tested. With models, we can determine the essence and consequences of different theoretical assumptions.

Models are a means of extrapolating from what is known to create proposals for more comprehensive theories with greater explanatory power. They are sample proposals that may or may not prove correct once experiments allow us to delve into smaller distances or higher energies and test their underlying hypotheses and predictions.

Bear in mind that a “theory” is different from a “model.” By the word theory, I don’t mean rough speculations, as in more colloquial usage. The known particles and the known physical laws they obey are components of a theory—a definite set of elements and principles with rules and equations for predicting how the elements interact.

But even when we fully understand a theory and its implications, that same theory can be implemented in many different ways, and these will have different physical consequences in the real world. Models are a way of sampling these possibilities. We combine known physical principles and elements into candidate descriptions of reality.

If you think of a theory as a PowerPoint template, a model would be your particular presentation. The theory allows animations, but the model includes only those you need to make your point. The theory would say to have a title and some bullet points, but the model would contain exactly what you want to convey and will hopefully apply well to the task at hand.

The nature of model building in physics has changed according to the questions physicists have tried to answer. Physics always involves trying to predict the largest number of physical quantities from the smallest number of assumptions, but that doesn’t mean we manage to identify the most fundamental theories right away. Advances in physics are often made even before everything is understood at the most fundamental level.

In the nineteenth century, physicists understood the notions of temperature and pressure and employed them in thermodynamics and engine design long before anyone could explain these ideas at a more fundamental microscopic level as the result of the random motion of large numbers of atoms and molecules. In the early twentieth century, physicists tried to make models to explain mass in terms of electromagnetic energy. Though these models were based on strongly shared beliefs on how those systems worked, those models proved wrong. A little later, Niels Bohr made a model of the atom to explain the emission spectra that people had observed. His model was soon superseded by the more comprehensive theory of quantum mechanics, which absorbed but also improved on Bohr’s core idea.

Model builders today try to determine what lies beyond the Standard Model of particle physics. Although currently referred to as the Standard Model because it has been well tested and is well understood, it was something of a guess as to how known observations might fit together at the time it was developed. Nonetheless, because the Standard Model implied predictions for how to test its premises, experiments could ultimately show it to be correct.

The Standard Model correctly accounts for all observations to date, but physicists are fairly confident that it is not complete. In particular, it leaves open the question of what are the precise particles and interactions—the elements of the Higgs sector—that are responsible for the masses of elementary particles and why it is that the particles in that sector have the particular masses that they do. Models that go beyond the Standard Model illuminate deeper potential interconnections and relationships that might address these questions. They involve specific choices of fundamental assumptions and physical concepts, as well as the distance or energy scales at which they might apply.

Much of my current research involves thinking about new models, as well as novel or more detailed search strategies that would otherwise miss new phenomena. I think about the models I originated but the full range of other possibilities as well. Particle physicists know the types of elements and rules that could be involved, such as particles, forces, and allowed interactions. But we don’t know precisely which of these ingredients enters the recipe for reality. By applying known theoretical ingredients, we attempt to identify the potentially simple underlying ideas that enter into what is an ultimately complex theory.

As important, models provide targets for experimental exploration, and suggestions for how particles will behave at smaller distances than physicists have experimentally studied so far. Measurements provide clues to help us distinguish among competing candidates. We don’t yet know what the new underlying theory is, but we can nonetheless characterize the possible deviations from the Standard Model. By thinking about candidate models for underlying reality and their consequences, we can predict what the LHC should reveal if the models turn out to be right. Our use of models admits the speculative nature of our ideas and recognizes the plethora of possibilities that might agree with existing data and explain as-yet-puzzling phenomena. Only some models will prove correct, but creating and understanding them is the best way to delineate the options and build up a reservoir of compelling ingredients.

Exploring models and their detailed consequences helps us establish what experimenters should search for—whatever might be out there. Models tell experimenters the interesting features that characterize new physical theories so that experimenters can test whether model builders have correctly identified the elements or the physical principles that guide the system’s relationships and interactions. Any model with new physical laws that apply at measurable energies should predict new particles and new relationships among them. Observing which particles emerge from collisions and the properties they have should help determine the type of particles that exist, their masses, and their interactions. Finding new particles or measuring different interactions will confirm or rule out models that have been proposed, and pave the way for better ones.

With enough data, experiments will determine which underlying model is the right one—at least at the level of precision, distance, and energy that we can study. The hope is that at the smallest distance scales that we can probe at LHC energies, the rules for the underlying theory will be simple enough to allow us to deduce and calculate the influence of the associated physical laws.

Physicists have lively discussions about which are the best models to study and what is the most useful way to account for them in experimental searches. I’ll frequently sit down with experimental colleagues and discuss with them how best to use models to guide their searches. Are benchmark points with specific parameters in particular models too specific? Is there a better way to cover all the possibilities?

LHC experiments are so challenging that without definite search targets, the results will be overwhelmed by Standard Model background. Experiments were designed and optimized with existing models in mind, but they are searching for more general possibilities as well. It is critical that experimenters are aware of a big range of models that span the possible new signatures that might emerge, since no one wants specific models to overly prejudice the searches.

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