Author Archives: Nicole Yunger Halpern

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About Nicole Yunger Halpern

I’m a theoretical physicist at the Joint Center for Quantum Information and Computer Science in Maryland. My research group re-envisions 19th-century thermodynamics for the 21st century, using the mathematical toolkit of quantum information theory. We then apply quantum thermodynamics as a lens through which to view the rest of science. I call this research “quantum steampunk,” after the steampunk genre of art and literature that juxtaposes Victorian settings (à la thermodynamics) with futuristic technologies (à la quantum information). For more information, check out my book for the general public, Quantum Steampunk: The Physics of Yesterday’s Tomorrow. I earned my PhD at Caltech under John Preskill’s auspices; one of my life goals is to be the subject of one of his famous (if not Pullitzer-worthy) poems. Follow me on Twitter @nicoleyh11.

Always look on the bright side…of CPTP maps.

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http://www.google.com/imgres?imgurl=http://www.stmoroky.com/reviews/films/brian.jpg&imgrefurl=http://www.stmoroky.com/reviews/films/brian.htm&h=290&w=250&tbnid=ZVAVf4ZX_zMISM:&zoom=1&docid=D5VZDH_bepBS0M&hl=en&ei=3bLfVIiYOoSpogS6toLYCQ&tbm=isch&ved=0CFEQMygYMBg

Once upon a time, I worked with a postdoc who shaped my views of mathematical physics, research, and life. Each week, I’d email him a PDF of the calculations and insights I’d accrued. He’d respond along the lines of, “Thanks so much for your notes. They look great! I think they’re mostly correct; there are just a few details that might need fixing.” My postdoc would point out the “details” over espresso, at a café table by a window. “Are you familiar with…?” he’d begin, and pull out of his back pocket some bit of math I’d never heard of. My calculations appeared to crumble like biscotti.

Some of the math involved CPTP maps. “CPTP” stands for a phrase little more enlightening than the acronym: “completely positive trace-preserving”. CPTP maps represent processes undergone by quantum systems. Imagine preparing some system—an electron, a photon, a superconductor, etc.—in a state I’ll call “\rho“. Imagine turning on a magnetic field, or coupling one electron to another, or letting the superconductor sit untouched. A CPTP map, labeled as \mathcal{E}, represents every such evolution.

“Trace-preserving” means the following: Imagine that, instead of switching on the magnetic field, you measured some property of \rho. If your measurement device (your photodetector, spectrometer, etc.) worked perfectly, you’d read out one of several possible numbers. Let p_i denote the probability that you read out the i^{\rm{th}} possible number. Because your device outputs some number, the probabilities sum to one: \sum_i p_i = 1.  We say that \rho “has trace one.” But you don’t measure \rho; you switch on the magnetic field. \rho undergoes the process \mathcal{E}, becoming a quantum state \mathcal{E(\rho)}. Imagine that, after the process ended, you measured a property of \mathcal{E(\rho)}. If your measurement device worked perfectly, you’d read out one of several possible numbers. Let q_a denote the probability that you read out the a^{\rm{th}} possible number. The probabilities sum to one: \sum_a q_a =1. \mathcal{E(\rho)} “has trace one”, so the map \mathcal{E} is “trace preserving”.

Now that we understand trace preservation, we can understand positivity. The probabilities p_i are positive (actually, nonnegative) because they lie between zero and one. Since the p_i characterize a crucial aspect of \rho, we call \rho “positive” (though we should call \rho “nonnegative”). \mathcal{E} turns the positive \rho into the positive \mathcal{E(\rho)}. Since \mathcal{E} maps positive objects to positive objects, we call \mathcal{E} “positive”. \mathcal{E} also satisfies a stronger condition, so we call such maps “completely positive.”**

So I called my postdoc. “It’s almost right,” he’d repeat, nudging aside his espresso and pulling out a pencil. We’d patch the holes in my calculations. We might rewrite my conclusions, strengthen my assumptions, or prove another lemma. Always, we salvaged cargo. Always, I learned.

I no longer email weekly updates to a postdoc. But I apply what I learned at that café table, about entanglement and monotones and complete positivity. “It’s almost right,” I tell myself when a hole yawns in my calculations and a week’s work appears to fly out the window. “I have to fix a few details.”

Am I certain? No. But I remain positive.

*Experts: “Trace-preserving” means \rm{Tr}(\rho) =1 \Rightarrow \rm{Tr}(\mathcal{E}(\rho)) = 1.

**Experts: Suppose that ρ is defined on a Hilbert space H and that E of rho is defined on H'. “Channel is positive” means Positive

To understand what “completely positive” means, imagine that our quantum system interacts with an environment. For example, suppose the system consists of photons in a box. If the box leaks, the photons interact with the electromagnetic field outside the box. Suppose the system-and-environment composite begins in a state SigmaAB defined on a Hilbert space HAB. Channel acts on the system’s part of state. Let I denote the identity operation that maps every possible environment state to itself. Suppose that Channel changes the system’s state while I preserves the environment’s state. The system-and-environment composite ends up in the state Channel SigmaAB. This state is positive, so we call Channel “completely positive”:Completely pos

Democrat plus Republican over the square-root of two

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I wish I could superpose votes on Election Day.

However much I agree with Candidate A about social issues, I dislike his running mate. I lean toward Candidate B’s economic plans and C’s science-funding record, but nobody’s foreign policy impresses me. Must I settle on one candidate? May I not vote

TeXVoteClip

Now you can—at least in theory. Caltech postdoc Ning Bao and I concocted quantum elections in which voters can superpose, entangle, and create probabilistic mixtures of votes.

Previous quantum-voting work has focused on privacy and cryptography. Ning and I channeled quantum game theory. Quantum game theorists ask what happens if players in classical games, such as the Prisoner’s Dilemma, could superpose strategies and share entanglement. Quantization can change the landscape of possible outcomes.

The Prisoner’s Dilemma, for example, concerns two thugs whom the police have arrested and have isolated in separate cells. Each prisoner must decide whether to rat out the other. How much time each serves depends on who, if anyone, confesses. Since neither prisoner knows the other’s decision, each should rat to minimize his or her jail time. But both would serve less time if neither confessed. The prisoners can escape this dilemma using quantum resources.

Introducing superpositions and entanglement into games helps us understand the power of quantum mechanics. Elections involve gameplay; pundits have been feeding off Hilary Clinton’s for months. So superpositions and entanglement merit introduction into elections.

How can you model elections with quantum systems? Though multiple options exist, Ning and I followed two principles: (1) A general quantum process—a preparation procedure, an evolution, and a measurement—should model a quantum election. (2) Quantum elections should remain as true as possible to classical.

Given our quantum voting system, one can violate a quantum analogue of Arrow’s Impossibility Theorem. Arrow’s Theorem, developed by the Nobel-winning economist Kenneth Arrow during the mid-20th century, is a no-go theorem about elections: If a constitution has three innocuous-seeming properties, it’s a dictatorship. Ning and I translated the theorem as faithfully as we knew how into our quantum voting scheme. The result, dubbed the Quantum Arrow Conjecture, rang false.

Superposing (and probabilistically mixing) votes entices me for a reason that science does: I feel ignorant. I read articles and interview political junkies about national defense; but I miss out on evidence and subtleties. I read quantum-physics books and work through papers; but I miss out on known mathematical tools and physical interpretations. Not to mention tools and interpretations that humans haven’t discovered.

Science involves identifying (and diminishing) what humanity doesn’t know. Science frees me to acknowledge my ignorance. I can’t throw all my weight behind Candidate A’s defense policy because I haven’t weighed all the arguments about defense, because I don’t know all the arguments. Believing that I do would violate my job description. How could I not vote for elections that accommodate superpositions?

Though Ning and I identified applications of superpositions and entanglement, more quantum strategies might await discovery. Monogamy of entanglement, discussed elsewhere on this blog, might limit the influence voters exert on each other. Also, we quantized ordinal voting systems (in which each voter ranks candidates, as in “A above C above B”). The quantization of cardinal voting (in which each voter grades the candidates, as in “5 points to A, 3 points to C, 2 points to B”) or another voting scheme might yield more insights.

If you have such insights, drop us a line. Ideally before the presidential smack-down of 2016.

Actions do change the world.

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I heard it in a college lecture about Haskell.

Haskell is a programming language akin to Latin: Learning either language expands your vocabulary and technical skills. But programmers use Haskell as often as slam poets compose dactylic hexameter.*

My professor could have understudied for the archetypal wise man: He had snowy hair, a beard, and glasses that begged to be called “spectacles.” Pointing at the code he’d projected onto a screen, he was lecturing about input/output, or I/O. The user inputs a request, and the program outputs a response.

That autumn was consuming me. Computer-science and physics courses had filled my plate. Atop the plate, I had thunked the soup tureen known as “XKCD Comes to Dartmouth”: I was coordinating a visit by Randall Munroe, creator of the science webcomic xkcd, to my college. The visit was to include a cake shaped like the Internet, a robotic velociraptor, and playpen balls.  The output I’d promised felt offputting.

My professor knew. We sat in his office for hours each week, dispatching my questions about recursion and monads and complexity. His input shaped the functional-programming skills I apply today, and my input shaped his lecture notes. He promised to attend my event.

Most objects coded in Haskell, my professor reminded us in that lecture, remain static. The Haskell world never changes. Even the objects called “variables” behave like constants. Exceptions, my professor said, crop up in I/O. Users can affect a program through objects called “actions.”

“Actions,” he said, “do change the world.”

I caught my breath. What a zinger, I thought. What a moral. What a lesson for the ages—and from the mouths of computer scientists.

My professor had no idea. He swanned on about I/O without changing tone.

That December, I gave my professor a plaque that read, “Actions do change the world.” Around his slogan, I’d littered illustrations of fractals, Pascal’s triangle, and other subjects we’d studied. My professor’s actions had changed my world for the better.

Drysdale photo 2

You can change the world by writing code that revolutionizes physics or finance. You can change the world by writing code that limps through tasks but improves your understanding. You can change the world by helping someone understand code. You can change the world by understanding someone.

A new year is beginning. Which actions will you take?

 

*Not that I recommend studying Haskell to boost your verbal SAT score.

I spy with my little eye…something algebraic.

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Look at this picture.

Peter 1

Does any part of it surprise you? Look more closely.

Peter 2

Now? Try crossing your eyes.

Peter 3

Do you see a boy’s name?

I spell “Peter” with two e’s, but “Piotr” and “Pyotr” appear as authors’ names in papers’ headers. Finding “Petr” in a paper shouldn’t have startled me. But how often does “Gretchen” or “Amadeus” materialize in an equation?

When I was little, my reading list included Eye Spy, Where’s Waldo?, and Puzzle Castle. The books teach children to pay attention, notice details, and evaluate ambiguities.

That’s what physicists do. The first time I saw the picture above, I saw a variation on “Peter.” I was reading (when do I not?) about the intersection of quantum information and thermodynamics. The authors were discussing heat and algebra, not saints or boys who picked pecks of pickled peppers. So I looked more closely.

Each letter resolved into part of a story about a physical system. The P represents a projector. A projector is a mathematical object that narrows one’s focus to a particular space, as blinders on a horse do. The E tells us which space to focus on: a space associated with an amount E of energy, like a country associated with a GDP of $500 billion.

Some of the energy E belongs to a heat reservoir. We know so because “reservoir” begins with r, and R appears in the picture. A heat reservoir is a system, like a colossal bathtub, whose temperature remains constant. The Greek letter \tau, pronounced “tau,” represents the reservoir’s state. The reservoir occupies an equilibrium state: The bath’s large-scale properties—its average energy, volume, etc.—remain constant. Never mind about jacuzzis.

Piecing together the letters, we interpret the picture as follows: Imagine a vast, constant-temperature bathtub (R). Suppose we shut the tap long enough ago that the water in the tub has calmed (\tau). Suppose the tub neighbors a smaller system—say, a glass of Perrier.* Imagine measuring how much energy the bath-and-Perrier composite contains (P). Our measurement device reports the number E.

Quite a story to pack into five letters. Didn’t Peter deserve a second glance?

The equation’s right-hand side forms another story. I haven’t seen Peters on that side, nor Poseidons nor Gallahads. But look closely, and you will find a story.

 

The images above appear in “Fundamental limitations for quantum and nanoscale thermodynamics,” published by Michał Horodecki and Jonathan Oppenheim in Nature Communications in 2013.

 

*Experts: The ρS that appears in the first two images represents the smaller system. The tensor product represents the reservoir-and-smaller-system composite.

Generally speaking

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My high-school calculus teacher had a mustache like a walrus’s and shoulders like a rower’s. At 8:05 AM, he would demand my class’s questions about our homework. Students would yawn, and someone’s hand would drift into the air.

“I have a general question,” the hand’s owner would begin.

“Only private questions from you,” my teacher would snap. “You’ll be a general someday, but you’re not a colonel, or even a captain, yet.”

Then his eyes would twinkle; his voice would soften; and, after the student asked the question, his answer would epitomize why I’ve chosen a life in which I use calculus more often than laundry detergent.

http://www.sell-buy-machines.com/2013/02/why-prefer-second-hand-equipment-over-new.html

Many times though I witnessed the “general” trap, I fell into it once. Little wonder: I relish generalization as other people relish hiking or painting or Michelin-worthy relish. When inferring general principles from examples, I abstract away details as though they’re tomato stains. My veneration of generalization led me to quantum information (QI) theory. One abstract theory can model many physical systems: electrons, superconductors, ion traps, etc.

Little wonder that generalizing a QI model swallowed my summer.

QI has shed light on statistical mechanics and thermodynamics, which describe energy, information, and efficiency. Models called resource theories describe small systems’ energies, information, and efficiencies. Resource theories help us calculate a quantum system’s value—what you can and can’t create from a quantum system—if you can manipulate systems in only certain ways.

Suppose you can perform only operations that preserve energy. According to the Second Law of Thermodynamics, systems evolve toward equilibrium. Equilibrium amounts roughly to stasis: Averages of properties like energy remain constant.

Out-of-equilibrium systems have value because you can suck energy from them to power laundry machines. How much energy can you draw, on average, from a system in a constant-temperature environment? Technically: How much “work” can you draw? We denote this average work by < W >. According to thermodynamics, < W > equals the change ∆F in the system’s Helmholtz free energy. The Helmholtz free energy is a thermodynamic property similar to the energy stored in a coiled spring.

http://www.telegraph.co.uk/property/propertyadvice/jeffhowell/8013593/Home-improvements-Slime-does-come-out-in-the-wash.html

One reason to study thermodynamics?

Suppose you want to calculate more than the average extractable work. How much work will you probably extract during some particular trial? Though statistical physics offers no answer, resource theories do. One answer derived from resource theories resembles ∆F mathematically but involves one-shot information theory, which I’ve discussed elsewhere.

If you average this one-shot extractable work, you recover < W > = ∆F. “Helmholtz” resource theories recapitulate statistical-physics results while offering new insights about single trials.

Helmholtz resource theories sit atop a silver-tasseled pillow in my heart. Why not, I thought, spread the joy to the rest of statistical physics? Why not generalize thermodynamic resource theories?

The average work <W > extractable equals ∆F if heat can leak into your system. If heat and particles can leak, <W > equals the change in your system’s grand potential. The grand potential, like the Helmholtz free energy, is a free energy that resembles the energy in a coiled spring. The grand potential characterizes Bose-Einstein condensates, low-energy quantum systems that may have applications to metrology and quantum computation. If your system responds to a magnetic field, or has mass and occupies a gravitational field, or has other properties, <W > equals the change in another free energy.

A collaborator and I designed resource theories that describe heat-and-particle exchanges. In our paper “Beyond heat baths: Generalized resource theories for small-scale thermodynamics,” we propose that different thermodynamic resource theories correspond to different interactions, environments, and free energies. I detailed the proposal in “Beyond heat baths II: Framework for generalized thermodynamic resource theories.”

“II” generalizes enough to satisfy my craving for patterns and universals. “II” generalizes enough to merit a hand-slap of a pun from my calculus teacher. We can test abstract theories only by applying them to specific systems. If thermodynamic resource theories describe situations as diverse as heat-and-particle exchanges, magnetic fields, and polymers, some specific system should shed light on resource theories’ accuracy.

If you find such a system, let me know. Much as generalization pleases aesthetically, the detergent is in the details.

The experimentalist next door

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At 9:10 AM, the lab next door was blasting “Born to Be Wild.”

I was at Oxford, moonlighting as a visiting researcher during fall 2013. My hosts included quantum theorists in Townsend Laboratory, a craggy great-uncle of a building. Poke your head out of the theory office, and Experiment would flood your vision. Our neighbors included laser wielders, ion trappers, atom freezers, and yellow signs that warned, “DANGER OF DEATH.”

P1040564

Down the corridor in Townsend Laboratory.

Hardly the neighborhood Mr. Rogers had in mind.

The lab that shared a wall with our office blasted music. To clear my head of calculations and of Steppenwolf, I would roam the halls. Some of the halls, that is. Other halls had hazmat warnings instead of welcome mats. I ran into “RADIATION,” “FIRE HAZARD,” “STRONG MAGNETIC FIELDS,” “HIGH VOLTAGE,” and “KEEP THIS TOILET NEAT AND TIDY.” Repelled from half a dozen doors, I would retreat to the office. Kelly Clarkson would be cooing through the wall.

“We can hear them,” a theorist observed about the experimentalists, “but they can’t hear us.”

P1040552

Dangers lurked even in the bathroom.

Experiment should test, disprove, and motivate theories; and theory should galvanize and (according to some thinkers) explain experiments. But some theorists stray from experiment like North America from Pangaea.

The theoretical physics I’ve enjoyed is abstract. I rarely address platforms, particular physical systems in which theory might incarnate. Quantum-information platforms include electrons in magnetic fields, photons (particles of light), ion traps, quantum dots, and nuclei such as the ones that image internal organs in MRI machines.

Instead of addressing electrons and photons, I address mathematics and abstract physical concepts. Each of these concepts can incarnate in different forms in different platforms. Examples of such concepts include preparation procedures, evolutions, measurements, and memories. One preparation procedure defined by one piece of math can result from a constant magnetic field in one platform and from a laser in another. Abstractness has power, enabling one idea to describe diverse systems.

I’ve enjoyed wandering the hills and sampling the vistas of Theory Land. Yet the experimentalist next door cranked up the radio of reality in my mind. “We can hear them,” a theorist said. In Townsend Laboratory, I began listening. My Oxford collaborators and I interwove two theoretical frameworks that describe heat transferred and work performed on small scales. One framework, one-shot statistical mechanics, has guest-starred on this blog.

The other framework consists of fluctuation relations, which describe deviations from average behaviors by small physical systems. A quantum particle on one side of a wall has a tiny probability of tunneling through without boring any hole. Since the probability is tiny, the average particle doesn’t tunnel (during any reasonably short amount of time). When analyzing macroscopic systems—say, the roughly 1024 atoms that form your left thumbnail—we assume that every particle behaves like the average particle. We can’t when analyzing minuscule systems such as one short strand of DNA. Deviations from average behaviors appear in experimental data about small systems as they do not appear in data about large systems. Fluctuation relations help us understand those deviations.

My colleagues and I addressed “information,” “systems,” and “interactions.” We deployed abstract ideas, referencing platforms only when motivating our work. Then a collaborator challenged me to listen through the wall.

Experimentalists have tested fluctuation relations. Why not check whether their data supports our theory? At my friend’s urging, I contacted experimentalists who’d shown that DNA obeys a fluctuation relation. The experimentalists had unzipped and re-zipped single DNA molecules using optical tweezers, which resemble ordinary tweezers but involve lasers. Whenever the experimentalists pulled the DNA, they measured the force they applied. They concluded that their platform obeyed an abstract fluctuation theorem. The experimentalists generously shared their data, which supported our results.

http://www.europhysicsnews.org/articles/epn/abs/2010/02/epn20102p27/epn20102p27.html

Experimentalists unzipped and rezipped DNA to test fluctuation relations. This depiction of the set-up comes from this article.

My colleagues and I didn’t propose experiments. We didn’t explain why platforms had behaved in unexpected ways. We checked calculations with recycled data. But we ventured outside Theory Land. We learned that one-shot theory models systems modeled also by fluctuation relations, which govern experiments. This link from one-shot theory to experiment, like the forbidden corridors in Townsend Laboratory, invite exploration.

In Townsend, I didn’t suffer the electric shocks or the explosions advertised on the doors (though the hot water in the bathroom nearly burned me). I turned out not to need those shocks. Blasting rock music at 9:10 AM can wake even a theorist up to reality.

How Physics for Poets can boost your Physics GRE score

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As summer fades to autumn, prospective grad students are eyeing applications. Professors are suggesting courses, and seniors are preparing for Graduate Record Exams (GREs). American physics programs  (and a few programs abroad) require or encourage applicants to take the Physics GRE. If you’ve sighted physics grad school in your crosshairs, consider adding Physics for Poets (PFP) to your course list. Many colleges develop this light-on-the-math tour of physics history for non-majors. But Physics for Poets can boost your Physics GRE score while reinforcing the knowledge gained from your physics major.

My senior spring in college, PFP manifested as “PHYS 001/002: Understanding the Universe: From Atoms to the Big Bang.” The tallness of this order failed to daunt Marcelo Gleiser, a cosmologist whose lectures swayed with a rhythm like a Foucault pendulum. From creation myths and Greek philosophers, we proceeded via Copernicus and Kepler to Newton and the Enlightenment, Maxwell and electromagnetism, the Industrial Revolution and thermodynamics, Einstein’s relativity, and WWII and the first quantum revolution, ending with particle physics and cosmology. The course provided a history credit I needed. It offered a breather from problem sets, sandwiching my biophysics and quantum-computation lectures. Pragmatism aside, PHYS 2 showcased the grandness of the physicist’s legacy—of my legacy. PHYS 2 sharpened my determination to do that legacy justice. To do it justice, most of us must pass tests. Here’s how PFP can help.

http://ask.dartmouth.edu/categories/misc/55.html

(1) A Foucault pendulum, invented during the 19th century to demonstrate that the Earth rotates. (2) An excuse to review noninertial reference frames.

Reviewing basic physics can improve GRE scores. If thermodynamics has faded from memory, good luck calculating a Carnot engine’s efficiency. Several guides (and I) recommend reviewing notes and textbooks, working practice problems, simulating exams, and discussing material with peers.

Taking PFP, you will review for the GRE. A list of the topics on the Physics GRE appears here. Of the 14 mechanics topics, eight surfaced in PHYS 2. Taking PFP will force you to review GRE topics that lack of time (or that procrastination) might force you to skip. Earning credit for GRE prep, you won’t have to shoehorn that prep into your schedule at the expense of research. The Physics GRE covers basic physics developed during the past 500 years; so do many PFP courses.

The GRE, you might protest, involves more math than PFP. But GRE questions probe less deeply, and PFP can galvanize more reviews of math, than you might expect. According to Stanford’s Society of Physics Students, “Each [Physics GRE] question shouldn’t require much more than a minute’s worth of thought and computation.” Expect to use the Wave Equation and Maxwell’s Equations, not to derive the former from the latter. Some PFP instructors require students to memorize formulae needed on the GRE. PFP can verify whether your memory has interchanged the exponents in Kepler’s Third Law, or dropped the negative sign from the kinetic-energy term in Schrödinger’s Equation.

Even formulae excluded from PFP exams appear in PFP classes. In a PHYS 2 Powerpoint, Marcelo included Planck’s blackbody formula. Though he never asked me to regurgitate it, his review benefited me. Given such a Powerpoint, you can re-memorize the formula. Derive the Stefan-Boltzmann and Wien Displacement Laws. Do you remember how a blackbody’s energy density varies with frequency in the low-energy limit? PFP can catalyze your review of math used on the GRE.

xkcd - Science

Physics for Poets: It can work for applicants to physics grad programs.

While recapitulating basic physics, PFP can introduce “specialized” GRE topics. Examples include particle physics, astrophysics, and nuclear physics. Covered in advanced classes, these subjects might have evaded mention in your courses. Signing up for biophysics, I had to drop particle theory. PHYS 2 helped compensate for the drop. I learned enough about neutrinos and quarks to answer GRE questions about them. In addition to improving your score, surveying advanced topics in PFP can enhance your understanding of physics seminars and conversations. The tour can help you identify which research you should undertake. If you’ve tried condensed-matter and atmospheric research without finding your niche, tasting cosmology in PFP might point toward your next project. Sampling advanced topics in PFP, you can not only prepare for the GRE, but also enrich your research.

I am not encouraging you to replace advanced physics courses with PFP. I encourage you to complement advanced courses with PFP. If particle physics suits your schedule and intrigues you, enjoy. If you need to fulfill a history or social-sciences distribution requirement, check whether PFP can count. Consider PFP if you’ve committed to a thesis and three problem-set courses, you haven’t signed up for the minimum number of courses required by your college, and more problem sets would strangle you. Sleep deprivation improves neither exam scores nor understanding. Not that I sailed through PHYS 2 without working. I worked my rear off—fortunately for my science. Switching mindsets—pausing frustrating calculations to study Kepler—can refresh us. Stretch your calculational toolkit in advanced courses, and reinforce that toolkit with PFP.

In addition to reviewing basic physics and surveying specialized topics, you can seek study help from experts in PFP. When your questions about GRE topics overlap with PFP material, ask your instructor and TA. They’ll probably enjoy answering: Imagine teaching physics with little math, with one hand tied behind your back. Some students take your class not because they want to, but because they need science credits. Wouldn’t you enjoy directing a student who cares? While seeking answers, you can get to know your professor or TA. You can learn about his or her research. Maybe PFP will lead you to join that research. PFP not only may connect you to experts able to answer questions as no study guide can. PFP offers opportunities to enhance a course as few non-physics students can and to develop relationships with role models.

Science class

Instructors’ expertise has benefited science students throughout much of history.

Those relationships illustrate the benefits that PFP extends beyond GREs. As mentioned earlier, surveying advanced topics can diversify the research conversations you understand. The survey can direct you toward research you’ll pursue. Further exposure to research can follow from discussions with instructors. Intermissions from problem sets can promote efficiency. Other benefits of PFP include enhancement of explanatory skills and a bird’s-eye view of the scientific process to which you’re pledging several years. What a privilege we enjoy, PFP shows. We physicists explore questions asked for millennia. We wear mantles donned by Faraday, Bernoulli, and Pauli. When integrals pour out our ears and experiments break down, PFP can remind us why we bother. And that we’re in fine company.

Physics for Poets can improve your Physics GRE score and reinforce your physics major. Surveying basic physics, PFP will force you to review GRE topics. PFP may introduce specialized GRE topics absent from most physics majors. Opportunities abound to re-memorize equations and to complement lectures with math. Questioning instructors, you can deepen your understanding as with no study guide. Beyond boosting your GRE score, PFP can broaden your research repertoire, energize your calculations, improve your explanatory skills, and inspire.

Good luck with the academic year, and see you in grad school!

Reading the sub(linear) text

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Physicists are not known for finesse. “Even if it cost us our funding,” I’ve heard a physicist declare, “we’d tell you what we think.” Little wonder I irked the porter who directed me toward central Cambridge.

The University of Cambridge consists of colleges as the US consists of states. Each college has a porter’s lodge, where visitors check in and students beg for help after locking their keys in their rooms. And where physicists ask for directions.

Last March, I ducked inside a porter’s lodge that bustled with deliveries. The woman behind the high wooden desk volunteered to help me, but I asked too many questions. By my fifth, her pointing at a map had devolved to jabbing.

Read the subtext, I told myself. Leave.

Or so I would have told myself, if not for that afternoon.

That afternoon, I’d visited Cambridge’s CMS, which merits every letter in “Centre for Mathematical Sciences.” Home to Isaac Newton’s intellectual offspring, the CMS consists of eight soaring, glass-walled, blue-topped pavilions. Their majesty walloped me as I turned off the road toward the gatehouse. So did the congratulatory letter from Queen Elizabeth II that decorated the route to the restroom.

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I visited Nilanjana Datta, an affiliated lecturer of Cambridge’s Faculty of Mathematics, and her student, Felix Leditzky. Nilanjana and Felix specialize in entropies and one-shot information theory. Entropies quantify uncertainties and efficiencies. Imagine compressing many copies of a message into the smallest possible number of bits (units of memory). How few bits can you use per copy? That number, we call the optimal compression rate. It shrinks as the number of copies compressed grows. As the number of copies approaches infinity, that compression rate drops toward a number called the message’s Shannon entropy. If the message is quantum, the compression rate approaches the von Neumann entropy.

Good luck squeezing infinitely many copies of a message onto a hard drive. How efficiently can we compress fewer copies? According to one-shot information theory, the answer involves entropies other than Shannon’s and von Neumann’s. In addition to describing data compression, entropies describe the charging of batteries, the concentration of entanglement, the encrypting of messages, and other information-processing tasks.

Speaking of compressing messages: Suppose one-shot information theory posted status updates on Facebook. Suppose that that panel on your Facebook page’s right-hand side showed news weightier than celebrity marriages. The news feed might read, “TRENDING: One-shot information theory: Second-order asymptotics.”

Second-order asymptotics, I learned at the CMS, concerns how the optimal compression rate decays as the number of copies compressed grows. Imagine compressing a billion copies of a quantum message ρ. The number of bits needed about equals a billion times the von Neumann entropy HvN(ρ). Since a billion is less than infinity, 1,000,000,000 HvN(ρ) bits won’t suffice. Can we estimate the compression rate more precisely?

The question reminds me of gas stations’ hidden pennies. The last time I passed a station’s billboard, some number like $3.65 caught my eye. Each gallon cost about $3.65, just as each copy of ρ costs about HvN(ρ) bits. But a 9/10, writ small, followed the $3.65. If I’d budgeted $3.65 per gallon, I couldn’t have filled my tank. If you budget HvN(ρ) bits per copy of ρ, you can’t compress all your copies.

Suppose some station’s owner hatches a plan to promote business. If you buy one gallon, you pay $3.654. The more you purchase, the more the final digit drops from four. By cataloguing receipts, you calculate how a tank’s cost varies with the number of gallons, n. The cost equals $3.65 × n to a first approximation. To a second approximation, the cost might equal $3.65 × n + a√n, wherein a represents some number of cents. Compute a, and you’ll have computed the gas’s second-order asymptotics.

Nilanjana and Felix computed a’s associated with data compression and other quantum tasks. Second-order asymptotics met information theory when Strassen combined them in nonquantum problems. These problems developed under attention from Hayashi, Han, Polyanski, Poor, Verdu, and others. Tomamichel and Hayashi, as well as Li, introduced quantumness.

In the total-cost expression, $3.65 × n depends on n directly, or “linearly.” The second term depends on √n. As the number of gallons grows, so does √n, but √n grows more slowly than n. The second term is called “sublinear.”

Which is the word that rose to mind in the porter’s lodge. I told myself, Read the sublinear text.

Little wonder I irked the porter. At least—thanks to quantum information, my mistake, and facial expressions’ contagiousness—she smiled.

 

 

With thanks to Nilanjana Datta and Felix Leditzky for explanations and references; to Nilanjana, Felix, and Cambridge’s Centre for Mathematical Sciences for their hospitality; and to porters everywhere for providing directions.

“Feveral kinds of hairy mouldy fpots”

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The book had a sheepskin cover, and mold was growing on the sheepskin. Robert Hooke, a pioneering microbiologist, slid the cover under one of the world’s first microscopes. Mold, he discovered, consists of “nothing elfe but feveral kinds of fmall and varioufly figur’d Mufhroms.” He described the Mufhroms in his treatise Micrographia, a 1665 copy of which I found in “Beautiful Science.” An exhibition at San Marino’s Huntington Library, “Beautiful Science” showcases the physics of rainbows, the stars that enthralled Galileo, and the world visible through microscopes.

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Beautiful science of yesterday: An illustration, from Hooke’s Micrographia, of the mold.

“[T]hrough a good Microfcope,” Hooke wrote, the sheepskin’s spots appeared “to be a very pretty fhap’d Vegetative body.”

How like a scientist, to think mold pretty. How like quantum noise, I thought, Hooke’s mold sounds.

Quantum noise hampers systems that transmit and detect light. To phone a friend or send an email—“Happy birthday, Sarah!” or “Quantum Frontiers has released an article”—we encode our message in light. The light traverses a fiber, buried in the ground, then hits a detector. The detector channels the light’s energy into a current, a stream of electrons that flows down a wire. The variations in the current’s strength is translated into Sarah’s birthday wish.

If noise doesn’t corrupt the signal. From encoding “Happy birthday,” the light and electrons might come to encode “Hsappi birthdeay.” Quantum noise arises because light consists of packets of energy, called “photons.” The sender can’t control how many photons hit the detector.

To send the letter H, we send about 108 photons.* Imagine sending fifty H’s. When we send the first, our signal might contain 108– 153 photons; when we send the second, 108 + 2,083; when we send the third, 108 – 6; and so on. Receiving different numbers of photons, the detector generates different amounts of current. Different amounts of current can translate into different symbols. From H, our message can morph into G.

This spring, I studied quantum noise under the guidance of IQIM faculty member Kerry Vahala. I learned to model quantum noise, to quantify it, when to worry about it, and when not. From quantum noise, we branched into Johnson noise (caused by interactions between the wire and its hot environment); amplified-spontaneous-emission, or ASE, noise (caused by photons belched by ions in the fiber); beat noise (ASE noise breeds with the light we sent, spawning new noise); and excess noise (the “miscellaneous” folder in the filing cabinet of noise types).

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Beautiful science of today: A microreso-nator—a tiny pendulum-like device— studied by the Vahala group.

Noise, I learned, has structure. It exhibits patterns. It has personalities. I relished studying those patterns as I relish sending birthday greetings while battling noise. Noise types, I see as a string of pearls unearthed in a junkyard. I see them as “pretty fhap[es]” in Hooke’s treatise. I see them—to pay a greater compliment—as “hairy mouldy fpots.”

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*Optical-communications ballpark estimates:

  • Optical power: 1 mW = 10-3 J/s
  • Photon frequency: 200 THz = 2 × 1014 Hz
  • Photon energy: h𝜈 = (6.626 × 10-34 J . s)(2 × 1014 Hz) = 10-19 J
  • Bit rate: 1 GB = 109 bits/s
  • Number of bits per H: 10
  • Number of photons per H: (1 photon / 10-19 J) (10-3 J/s)(1 s / 109 bits)(10 bits / 1 H) = 108

 

An excerpt from this post was published today on Verso, the blog of the Huntington Library, Art Collection, and Botanical Gardens.

With thanks to Bassam Helou, Dan Lewis, Matt Stevens, and Kerry Vahala for feedback. With thanks to the Huntington Library (including Catherine Wehrey) and the Vahala group for the Micrographia image and the microresonator image, respectively.

Clocking in at a Cambridge conference

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Science evolves on Facebook.

On Facebook last fall, I posted about statistical mechanics. Statistical mechanics is the physics of hordes of particles. Hordes of molecules, for example, form the stench seeping from a clogged toilet. Hordes change in certain ways but not in the reverse ways, suggesting time points in a direction. Once a stink diffuses into the hall, it won’t regroup in the bathroom. The molecules’ locations distinguish past from future.

The post attracted a comment by Ian Durham, associate professor of physics at St. Anselm College. Minutes later, we were instant-messaging about infinitely long evolutions.* The next day, I sent Ian a paper draft. His reply made me jump more than a whiff of a toilet would. Would I discuss the paper at a conference he was co-organizing?

I almost replied, Are you sure?

Then I almost replied, Yes, please!

The conference, “Eddington and Wheeler: Information and Interaction,” unfolded this March at the University of Cambridge. Cambridge employed Sir Arthur Eddington, the astronomer whose 1919 observation of starlight during an eclipse catapulted Einstein’s general relativity to fame. Decades later, John Wheeler laid groundwork for quantum information. Though aware of Eddington’s observation, I hadn’t known he’d researched stat mech. I hadn’t known his opinions about time. Time owns a high-rise in my heart; see the fussiness with which I catalogue “last fall,” “minutes later,” and “the next day.” Conference-goers shared news about time in the Old Combination Room at Cambridge’s Trinity College. Against the room’s wig-filled portraits, our projector resembled a souvenir misplaced by a time traveler.

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Trinity College, Cambridge.

Presenter one, Huw Price, argued that time has no arrow. It appears to in our universe: We remember the past and anticipate the future. Once a stench diffuses, it doesn’t regroup. The stench illustrates the Second Law of Thermodynamics, the assumption that entropy increases.

If “entropy” doesn’t ring a bell, never mind; we’ll dissect it in future articles. Suffice it to say that (1) thermodynamics is a branch of physics related to stat mech; (2) according to the Second Law of Thermodynamics, something called “entropy” increases; (3) entropy’s rise distinguishes the past from the future by associating the former with a low entropy and the latter with a large entropy; and (4) a stench’s diffusion illustrates the Second Law and time’s flow.

In as many universes in which entropy increases (time flows in one direction), in so many universe does entropy decrease (does time flow oppositely). So, said Huw Price, postulated the 19th-century stat-mech founder Ludwig Boltzmann. Why would universes pair up? For the reason why, driving across a pothole, you not only fall, but also rise. Each fluctuation from equilibrium—from a flat road—involves an upward path and a downward. The upward path resembles a universe in which entropy increases; the downward, a universe in which entropy decreases. Every down pairs with an up. Averaged over universes, time has no arrow.

Freidel Weinert, presenter five, argued the opposite. Time has an arrow, he said, and not because of entropy.

Ariel Caticha discussed an impersonator of time. Using a cousin of MaxEnt, he derived an equation identical to Schrödinger’s. MaxEnt, short for “the Maximum Entropy Principle,” is a tool used in stat mech. Schrödinger’s Equation describes how quantum systems evolve. To draw from Schrödinger’s Equation predictions about electrons and atoms, physicists assume that features of reality resemble certain bits of math. We assume, for example, that the t in Schrödinger’s Equation represents time. A t appeared in Ariel’s twin of Schrödinger’s Equation. But Ariel didn’t assume what physicists usually assume. MaxEnt motivated his assumptions. Interpreting Ariel’s equation poses a challenge. If a variable acts like time and smells like time, does it represent time?**

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A presenter uses the anachronistic projector. The head between screen and camera belongs to David Finkelstein, who helped develop the theory of general relativity checked by Eddington.

Like Ariel, Bill Wootters questioned time’s role in arguments. The co-creator of quantum teleportation wondered why one tenet of quantum physics has the form it has. Using quantum mechanics, we can’t predict certain experiments’ outcomes. We can predict probabilities—the chance that some experiment will yield Possible Outcome 1, the chance that the experiment will yield Possible Outcome 2, and so on. To calculate these probabilities, we square numbers. Why square? Why don’t the probabilities depend on cubes?

To explore this question, Bill told a story. Suppose some experimenter runs these experiments on Monday and those on Tuesday. When evaluating his story, Bill pointed out a hole: Replacing “Monday” and “Tuesday” with “eight o’clock” and “nine” wouldn’t change his conclusion. Which replacements wouldn’t change it, and which would? To what can we generalize those days? We couldn’t answer his questions on the Sunday he asked them.

Little of presentation twelve concerned time. Rüdiger Schack introduced QBism, an interpretation of quantum mechanics that sounds like “cubism.” Casting quantum physics in terms of experimenters’ actions, Rüdiger mentioned time. By the time of the mention, I couldn’t tell what anyone meant by “time.” Raising a hand, I asked for clarification.

“You are young,” Rüdiger said. “But you will grow old and die.”

The comment clanged like the slam of a door. It echoed when I followed Ian into Ascension Parish Burial Ground. On Cambridge’s outskirts, conference-goers visited Eddington’s headstone. We found Wittgenstein’s near an uneven footpath; near tangles of undergrowth, Nobel laureates’. After debating about time, we marked its footprints. Paths of glory lead but to the grave.

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Here lies one whose name was writ in a conference title: Sir Arthur Eddington’s grave.

Paths touched by little glory, I learned, have perks. As Rüdiger noted, I was the greenest participant. As he had the manners not to note, I was the least distinguished and the most ignorant. Studenthood freed me to raise my hand, to request clarification, to lack opinions about time. Perhaps I’ll evolve opinions at some t, some Monday down the road. That Monday feels infinitely far off. These days, I’ll stick to evolving science—using that other boon of youth, Facebook.

*You know you’re a theoretical physicist (or a physicist-in-training) when you debate about processes that last till kingdom come.

** As long as the variable doesn’t smell like a clogged toilet.

For videos of the presentations—including the public lecture by best-selling author Neal Stephenson—stay tuned to http://informationandinteraction.wordpress.com. My presentation appears here. 

With gratitude to Ian Durham and Dean Rickles for organizing “Information and Interaction” and for the opportunity to participate. With thanks to the other participants for sharing their ideas and time.