About Nicole Yunger Halpern

I'm pursuing a physics PhD with the buccaneers of Quantum Frontiers. Before moving to Caltech, I studied at Dartmouth College and the Perimeter Institute for Theoretical Physics. I apply quantum-information tools to thermodynamics and statistical mechanics (the study of heat, work, information, and time), particularly at small scales. I like my quantum information physical, my math algebraic, and my spins rotated but not stirred.

Bringing the heat to Cal State LA

John Baez is a tough act to follow.

The mathematical physicist presented a colloquium at Cal State LA this May.1 The talk’s title: “My Favorite Number.” The advertisement image: A purple “24” superimposed atop two egg cartons.


The colloquium concerned string theory. String theorists attempt to reconcile Einstein’s general relativity with quantum mechanics. Relativity concerns the large and the fast, like the sun and light. Quantum mechanics concerns the small, like atoms. Relativity and with quantum mechanics individually suggest that space-time consists of four dimensions: up-down, left-right, forward-backward, and time. String theory suggests that space-time has more than four dimensions. Counting dimensions leads theorists to John Baez’s favorite number.

His topic struck me as bold, simple, and deep. As an otherworldly window onto the pedestrian. John Baez became, when I saw the colloquium ad, a hero of mine.

And a tough act to follow.

I presented Cal State LA’s physics colloquium the week after John Baez. My title: “Quantum steampunk: Quantum information applied to thermodynamics.” Steampunk is a literary, artistic, and film genre. Stories take place during the 1800s—the Victorian era; the Industrial era; an age of soot, grime, innovation, and adventure. Into the 1800s, steampunkers transplant modern and beyond-modern technologies: automata, airships, time machines, etc. Example steampunk works include Will Smith’s 1999 film Wild Wild West. Steampunk weds the new with the old.

So does quantum information applied to thermodynamics. Thermodynamics budded off from the Industrial Revolution: The steam engine crowned industrial technology. Thinkers wondered how efficiently engines could run. Thinkers continue to wonder. But the steam engine no longer crowns technology; quantum physics (with other discoveries) does. Quantum information scientists study the roles of information, measurement, and correlations in heat, energy, entropy, and time. We wed the new with the old.


What image could encapsulate my talk? I couldn’t lean on egg cartons. I proposed a steampunk warrior—cravatted, begoggled, and spouting electricity. The proposal met with a polite cough of an email. Not all department members, Milan Mijic pointed out, had heard of steampunk.

Steampunk warrior

Milan is a Cal State LA professor and my erstwhile host. We toured the palm-speckled campus around colloquium time. What, he asked, can quantum information contribute to thermodynamics?

Heat offers an example. Imagine a classical (nonquantum) system of particles. The particles carry kinetic energy, or energy of motion: They jiggle. Particles that bump into each other can exchange energy. We call that energy heat. Heat vexes engineers, breaking transistors and lowering engines’ efficiencies.

Like heat, work consists of energy. Work has more “orderliness” than the heat transferred by random jiggles. Examples of work exertion include the compression of a gas: A piston forces the particles to move in one direction, in concert. Consider, as another example, driving electrons around a circuit with an electric field. The field forces the electrons to move in the same direction. Work and heat account for all the changes in a system’s energy. So states the First Law of Thermodynamics.

Suppose that the system is quantum. It doesn’t necessarily have a well-defined energy. But we can stick the system in an electric field, and the system can exchange motional-type energy with other systems. How should we define “work” and “heat”?

Quantum information offers insights, such as via entropies. Entropies quantify how “mixed” or “disordered” states are. Disorder grows as heat suffuses a system. Entropies help us extend the First Law to quantum theory.

First slide

So I explained during the colloquium. Rarely have I relished engaging with an audience as much as I relished engaging with Cal State LA’s. Attendees made eye contact, posed questions, commented after the talk, and wrote notes. A student in a corner appeared to be writing homework solutions. But a presenter couldn’t have asked for more from the rest. One exclamation arrested me like a coin in the cogs of a grandfather clock.

I’d peppered my slides with steampunk art: paintings, drawings, stills from movies. The peppering had staved off boredom as I’d created the talk. I hoped that the peppering would stave off my audience’s boredom. I apologized about the trimmings.

“No!” cried a woman near the front. “It’s lovely!”

I was about to discuss experiments by Jukka Pekola’s group. Pekola’s group probes quantum thermodynamics using electronic circuits. The group measures heat by counting the electrons that hop from one part of the circuit to another. Single-electron transistors track tunneling (quantum movements) of single particles.

Heat complicates engineering, calculations, and California living. Heat scrambles signals, breaks devices, and lowers efficiencies. Quantum heat can evade definition. Thermodynamicists grind their teeth over heat.

“No!” the woman near the front had cried. “It’s lovely!”

She was referring to steampunk art. But her exclamation applied to my subject. Heat has not only practical importance, but also fundamental: Heat influences every law of thermodynamics. Thermodynamic law underpins much of physics as 24 underpins much of string theory. Lovely, I thought, indeed.

Cal State LA offered a new view of my subfield, an otherworldly window onto the pedestrian. The more pedestrian an idea—the more often the idea surfaces, the more of our world the idea accounts for—the deeper the physics. Heat seems as pedestrian as a Pokémon Go player. But maybe, someday, I’ll present an idea as simple, bold, and deep as the number 24.


A window onto Cal State LA.

With gratitude to Milan Mijic, and to Cal State LA’s Department of Physics and Astronomy, for their hospitality.

1For nonacademics: A typical physics department hosts several presentations per week. A seminar relates research that the speaker has undertaken. The audience consists of department members who specialize in the speaker’s subfield. A department’s astrophysicists might host a Monday seminar; its quantum theorists, a Wednesday seminar; etc. One colloquium happens per week. Listeners gather from across the department. The speaker introduces a subfield, like the correction of errors made by quantum computers. Course lectures target students. Endowed lectures, often named after donors, target researchers.

What matters to me, and why?

Students at my college asked every Tuesday. They gathered in a white, windowed room near the center of campus. “We serve,” read advertisements, “soup, bread, and food for thought.” One professor or visitor would discuss human rights, family,  religion, or another pepper in the chili of life.

I joined occasionally. I listened by the window, in the circle of chairs that ringed the speaker. Then I ventured from college into physics.

The questions “What matters to you, and why?” have chased me through physics. I ask experimentalists and theorists, professors and students: Why do you do science? Which papers catch your eye? Why have you devoted to quantum information more years than many spouses devote to marriages?

One physicist answered with another question. Chris Jarzynski works as a professor at the University of Maryland. He studies statistical mechanics—how particles typically act and how often particles act atypically; how materials shine, how gases push back when we compress them, and more.

“How,” Chris asked, “should we quantify precision?”

Chris had in mind nonequilibrium fluctuation theoremsOut-of-equilibrium systems have large-scale properties, like temperature, that change significantly.1 Examples include white-bean soup cooling at a “What matters” lunch. The soup’s temperature drops to room temperature as the system approaches equilibrium.

Steaming soup

Nonequilibrium. Tasty, tasty nonequilibrium.

Some out-of-equilibrium systems obey fluctuation theorems. Fluctuation theorems are equations derived in statistical mechanics. Imagine a DNA molecule floating in a watery solution. Water molecules buffet the strand, which twitches. But the strand’s shape doesn’t change much. The DNA is in equilibrium.

You can grab the strand’s ends and stretch them apart. The strand will leave equilibrium as its length changes. Imagine pulling the strand to some predetermined length. You’ll have exerted energy.

How much? The amount will vary if you repeat the experiment. Why? This trial began with the DNA curled this way; that trial began with the DNA curled that way. During this trial, the water batters the molecule more; during that trial, less. These discrepancies block us from predicting how much energy you’ll exert. But suppose you pick a number W. We can form predictions about the probability that you’ll have to exert an amount W of energy.

How do we predict? Using nonequilibrium fluctuation theorems.

Fluctuation theorems matter to me, as Quantum Frontiers regulars know. Why? Because I’ve written enough fluctuation-theorem articles to test even a statistical mechanic’s patience. More seriously, why do fluctuation theorems matter to me?

Fluctuation theorems fill a gap in the theory of statistical mechanics. Fluctuation theorems relate nonequilibrium processes (like the cooling of soup) to equilibrium systems (like room-temperature soup). Physicists can model equilibrium. But we know little about nonequilibrium. Fluctuation theorems bridge from the known (equilibrium) to the unknown (nonequilibrium).

Bridge - theory

Experiments take place out of equilibrium. (Stretching a DNA molecule changes the molecule’s length.) So we can measure properties of nonequilibrium processes. We can’t directly measure properties of equilibrium processes, which we can’t perform experimentally. But we can measure an equilibrium property indirectly: We perform nonequilibrium experiments, then plug our data into fluctuation theorems.

Bridge - exprmt

Which equilibrium property can we infer about? A free-energy difference, denoted by ΔF. Every equilibrated system (every room-temperature soup) has a free energy F. F represents the energy that the system can exert, such as the energy available to stretch a DNA molecule. Imagine subtracting one system’s free energy, F1, from another system’s free energy, F2. The subtraction yields a free-energy difference, ΔF = F2 – F1. We can infer the value of a ΔF from experiments.

How should we evaluate those experiments? Which experiments can we trust, and which need repeating?

Those questions mattered little to me, before I met Chris Jarzynski. Bridging equilibrium with nonequilibrium mattered to me, and bridging theory with experiment. Not experimental nitty-gritty.

I deserved a dunking in white-bean soup.

Dunk 2

Suppose you performed infinitely many trials—stretched a DNA molecule infinitely many times. In each trial, you measured the energy exerted. You processed your data, then substituted into a fluctuation theorem. You could infer the exact value of ΔF.

But we can’t perform infinitely many trials. Imprecision mars our inference about ΔF. How does the imprecision relate to the number of trials performed?2

Chris and I adopted an information-theoretic approach. We quantified precision with a parameter \delta. Suppose you want to estimate ΔF with some precision. How many trials should you expect to need to perform? We bounded the number N_\delta of trials, using an entropy. The bound tightens an earlier estimate of Chris’s. If you perform N_\delta trials, you can estimate ΔF with a percent error that we estimated. We illustrated our results by modeling a gas.

I’d never appreciated the texture and richness of precision. But richness precision has: A few decimal places distinguish Albert Einstein’s general theory of relativity from Isaac Newton’s 17th-century mechanics. Particle physicists calculate constants of nature to many decimal places. Such a calculation earned a nod on physicist Julian Schwinger’s headstone. Precision serves as the bread and soup of much physics. I’d sniffed the importance of precision, but not tasted it, until questioned by Chris Jarzynski.

Schwinger headstone

The questioning continues. My college has discontinued its “What matters” series. But I ask scientist after scientist—thoughtful human being after thoughtful human being—“What matters to you, and why?” Asking, listening, reading, calculating, and self-regulating sharpen my answers those questions. My answers often squish beneath the bread knife in my cutlery drawer of criticism. Thank goodness that repeating trials can reduce our errors.

Bread knife

1Or large-scale properties that will change. Imagine connecting the ends of a charged battery with a wire. Charge will flow from terminal to terminal, producing a current. You can measure, every minute, how quickly charge is flowing: You can measure how much current is flowing. The current won’t change much, for a while. But the current will die off as the battery nears depletion. A large-scale property (the current) appears constant but will change. Such a capacity to change characterizes nonequilibrium steady states (NESSes). NESSes form our second example of nonequilibrium states. Many-body localization forms a third, quantum example.

2Readers might object that scientists have tools for quantifying imprecision. Why not apply those tools? Because ΔF equals a logarithm, which is nonlinear. Other authors’ proposals appear in references 1-13 of our paper. Charlie Bennett addressed a related problem with his “acceptance ratio.” (Bennett also blogged about evil on Quantum Frontiers last month.)

Quantum braiding: It’s all in (and on) your head.

Morning sunlight illuminated John Preskill’s lecture notes. The notes concern Caltech’s quantum-computation course, Ph 219. I’m TAing (the teaching assistant for) Ph 219. I previewed lecture material one sun-kissed Sunday.

Pasadena sunlight spilled through my window. So did the howling of a dog that’s deepened my appreciation for Billy Collins’s poem “Another reason why I don’t keep a gun in the house.” My desk space warmed up, and I unbuttoned my jacket. I underlined a phrase, braided my hair so my neck could cool, and flipped a page.

I flipped back. The phrase concerned a mathematical statement called “the Yang-Baxter relation.” A sunbeam had winked on in my mind: The Yang-Baxter relation described my hair.

The Yang-Baxter relation belongs to a branch of math called “topology.” Topology resembles geometry in its focus on shapes. Topologists study spheres, doughnuts, knots, and braids.

Topology describes some quantum physics. Scientists are harnessing this physics to build quantum computers. Alexei Kitaev largely dreamed up the harness. Alexei, a Caltech professor, is teaching Ph 219 this spring.1 His computational scheme works like this.

We can encode information in radio signals, in letters printed on a page, in the pursing of one’s lips as one passes a howling dog’s owner, and in quantum particles. Imagine three particles on a tabletop.

Peas 1

Consider pushing the particles around like peas on a dinner plate. You could push peas 1 and 2 until they swapped places. The swap represents a computation, in Alexei’s scheme.2

The diagram below shows how the peas move. Imagine slicing the figure into horizontal strips. Each strip would show one instant in time. Letting time run amounts to following the diagram from bottom to top.

Peas 2

Arrows copied from John Preskill’s lecture notes. Peas added by the author.

Imagine swapping peas 1 and 3.

Peas 3

Humor me with one more swap, an interchange of 2 and 3.

Peas 4

Congratulations! You’ve modeled a significant quantum computation. You’ve also braided particles.

2 braids

The author models a quantum computation.

Let’s recap: You began with peas 1, 2, and 3. You swapped 1 with 2, then 1 with 3, and then 2 with 3. The peas end up ordered oppositely the way they began—end up ordered as 3, 2, 1.

You could, instead, morph 1-2-3 into 3-2-1 via a different sequence of swaps. That sequence, or braid, appears below.

Peas 5

Congratulations! You’ve begun proving the Yang-Baxter relation. You’ve shown that  each braid turns 1-2-3 into 3-2-1.

The relation states also that 1-2-3 is topologically equivalent to 3-2-1: Imagine standing atop pea 2 during the 1-2-3 braiding. You’d see peas 1 and 3 circle around you counterclockwise. You’d see the same circling if you stood atop pea 2 during the 3-2-1 braiding.

That Sunday morning, I looked at John’s swap diagrams. I looked at the hair draped over my left shoulder. I looked at John’s swap diagrams.

“Yang-Baxter relation” might sound, to nonspecialists, like a mouthful of tweed. It might sound like a sneeze in a musty library. But an eight-year-old could grasp the half the relation. When I braid my hair, I pass my left hand over the back of my neck. Then, I pass my right hand over. But I could have passed the right hand first, then the left. The braid would have ended the same way. The braidings would look identical to a beetle hiding atop what had begun as the middle hunk of hair.


The Yang-Baxter relation.

I tried to keep reading John’s lecture notes, but the analogy mushroomed. Imagine spinning one pea atop the table.

Pea 6

A 360° rotation returns the pea to its initial orientation. You can’t distinguish the pea’s final state from its first. But a quantum particle’s state can change during a 360° rotation. Physicists illustrate such rotations with corkscrews.


Pachos corkscrew 2

A quantum corkscrew (“twisted worldribbon,” in technical jargon)

Like the corkscrews formed as I twirled my hair around a finger. I hadn’t realized that I was fidgeting till I found John’s analysis.

Version 2

I gave up on his lecture notes as the analogy sprouted legs.

I’ve never mastered the fishtail braid. What computation might it represent? What about the French braid? You begin French-braiding by selecting a clump of hair. You add strands to the clump while braiding. The addition brings to mind particles created (and annihilated) during a topological quantum computation.

Ancient Greek statues wear elaborate hairstyles, replete with braids and twists.  Could you decode a Greek hairdo? Might it represent the first 18 digits in pi? How long an algorithm could you run on Rapunzel’s hair?

Call me one bobby pin short of a bun. But shouldn’t a scientist find inspiration in every fiber of nature? The sunlight spilling through a window illuminates no less than the hair spilling over a shoulder. What grows on a quantum physicist’s head informs what grows in it.


1Alexei and John trade off on teaching Ph 219. Alexei recommends the notes that John wrote while teaching in previous years.

2When your mother ordered you to quit playing with your food, you could have objected, “I’m modeling computations!”

little by little and gate by gate

Washington state was drizzling on me. I was dashing from a shuttle to Building 112 on Microsoft’s campus. Microsoft has headquarters near Seattle. The state’s fir trees refreshed me. The campus’s vastness awed me. The conversations planned for the day enthused me. The drizzle dampened me.

Building 112 houses QuArC, one of Microsoft’s research teams. “QuArC” stands for “Quantum Architectures and Computation.” Team members develop quantum algorithms and codes. QuArC members write, as their leader Dr. Krysta Svore says, “software for computers that don’t exist.”

Microsoft 2

Small quantum computers exist. Large ones have eluded us like gold at the end of a Washington rainbow. Large quantum computers could revolutionize cybersecurity, materials engineering, and fundamental physics. Quantum computers are growing, in labs across the world. When they mature, the computers will need software.

Software consists of instructions. Computers follow instructions as we do. Suppose you want to find and read the poem “anyone lived in a pretty how town,” by 20th-century American poet e e cummings. You follow steps—for example:

1) Wake up your computer.
2) Type your password.
3) Hit “Enter.”
4) Kick yourself for entering the wrong password.
5) Type the right password.
6) Hit “Enter.”
7) Open a web browser.
8) Navigate to Google.
9) Type “anyone lived in a pretty how town e e cummings” into the search bar.
10) Hit “Enter.”
11) Click the Academy of American Poets’ link.
12) Exclaim, “Really? April is National Poetry Month?”
13) Read about National Poetry Month for four-and-a-half minutes.
14) Remember that you intended to look up a poem.
15) Return to the Academy of American Poets’ “anyone lived” webpage.
16) Read the poem.

We break tasks into chunks executed sequentially. So do software writers. Microsoft researchers break up tasks intended for quantum computers to perform.

Your computer completes tasks by sending electrons through circuits. Quantum computers will have circuits. A circuit contains wires, which carry information. The wires run through circuit components called gates. Gates manipulate the information in the wires. A gate can, for instance, add the number carried by this wire to the number carried by that wire.

Running a circuit amounts to completing a task, like hunting a poem. Computer engineers break each circuit into wires and gates, as we broke poem-hunting into steps 1-16.1

Circuits hearten me, because decomposing tasks heartens me. Suppose I demanded that you read a textbook in a week, or create a seminar in a day, or crack a cybersecurity system. You’d gape like a visitor to Washington who’s realized that she’s forgotten her umbrella.


Suppose I demanded instead that you read five pages, or create one Powerpoint slide, or design one element of a quantum circuit. You might gape. But you’d have more hope.2 Life looks more manageable when broken into circuit elements.

Circuit decomposition—and life decomposition—brings to mind “anyone lived in a pretty how town.” The poem concerns two characters who revel in everyday events. Laughter, rain, and stars mark their time. The more the characters attune to nature’s rhythm, the more vibrantly they live:3

          little by little and was by was

          all by all and deep by deep
          and more by more they dream their sleep

Those lines play in my mind when a seminar looms, or a trip to Washington coincident with a paper deadline, or a quantum circuit I’ve no idea how to parse. Break down the task, I tell myself. Inch by inch, we advance. Little by little and drop by drop, step by step and gate by gate.

IBM circuit

Not what e e cummings imagined when composing “anyone lived in a pretty how town”

Unless you’re dashing through raindrops to gate designers at Microsoft. I don’t recommend inching through Washington’s rain. But I would have dashed in a drought. What sees us through everyday struggles—the inching of science—if not enthusiasm? We tackle circuits and struggles because, beyond the drizzle, lie ideas and conversations that energize us to run.


e e cummings

With thanks to QuArC members for their time and hospitality.

1One might object that Steps 4 and 14 don’t belong in the instructions. But software involves error correction.

2Of course you can design a quantum-circuit element. Anyone can quantum.

3Even after the characters die.

March madness and quantum memory

Madness seized me this March. It pounced before newspaper and Facebook feeds began buzzing about basketball.1 I haven’t bought tickets or bet on teams. I don’t obsess over jump-shot statistics. But madness infected me two weeks ago. I began talking with condensed-matter physicists.

Condensed-matter physicists study collections of many particles. Example collections include magnets and crystals. And the semiconductors in the iPhones that report NCAA updates.

Caltech professor Gil Refael studies condensed matter. He specializes in many-body localization. By “many-body,” I mean “involving lots of quantum particles.” By “localization,” I mean “each particle anchors itself to one spot.” We’d expect these particles to spread out, like the eau de hotdog that wafts across a basketball court. But Gil’s particles stay put.

Hot-dog smell

How many-body-localized particles don’t behave.

Experts call many-body localization “MBL.” I’ve accidentally been calling many-body localization “MLB.” Hence the madness. You try injecting baseball into quantum discussions without sounding one out short of an inning.2

I wouldn’t have minded if the madness had erupted in October. The World Series began in October. The World Series involves Major League Baseball, what normal people call “the MLB.” The MLB dominates October; the NCAA dominates March. Preoccupation with the MLB during basketball season embarrasses me. I feel like I’ve bet on the last team that I could remember winning the championship, then realized that that team had last won in 2002.

March madness has been infecting my thoughts about many-body localization. I keep envisioning a localized particle as dribbling a basketball in place, opponents circling, fans screaming, “Go for it!” Then I recall that I’m pondering MBL…I mean, MLB…or the other way around. The dribbler gives way to a baseball player who refuses to abandon first base for second. Then I recall that I should be pondering particles, not playbooks.

Baseball diamond

Localized particles.

Recollection holds the key to MBL’s importance. Colleagues of Gil’s want to build quantum computers. Computers store information in memories. Memories must retain their contents; information mustn’t dribble away.

Consider recording halftime scores. You could encode the scores in the locations of the particles that form eau de hotdog. (Imagine you have advanced technology that manipulates scent particles.) If Duke had scored one point, you’d put this particle here; if Florida had scored two, you’d put that particle there. The particles—as smells too often do—would drift. You’d lose the information you’d encoded. Better to paint the scores onto scorecards. Dry paint stays put, preserving information.

The quantum particles studied by Gil stay put. They inspire scientists who develop memories for quantum computers. Quantum computation is gunning for a Most Valuable Player plaque in the technology hall of fame. Many-body localized systems could contain Most Valuable Particles.

MVP medal

Remembering the past, some say, one can help one read the future. I don’t memorize teams’ records. I can’t advise you about whom root for. But prospects for quantum memories are brightening. Bet on quantum information science.

1Non-American readers: University basketball teams compete in a tournament each March. The National Collegiate Athletic Association (NCAA) hosts the tournament. Fans glue themselves to TVs, tweet exaltations and frustrations, and excommunicate friends who support opposing teams.

2Without being John Preskill.

Some like it cold.

When I reached IBM’s Watson research center, I’d barely seen Aaron in three weeks. Aaron is an experimentalist pursuing a physics PhD at Caltech. I eat dinner with him and other friends, most Fridays. The group would gather on a sidewalk in the November dusk, those three weeks. Light would spill from a lamppost, and we’d tuck our hands into our pockets against the chill. Aaron’s wife would shake her head.

“The fridge is running,” she’d explain.

Aaron cools down mechanical devices to near absolute zero. Absolute zero is the lowest temperature possible,1 lower than outer space’s temperature. Cold magnifies certain quantum behaviors. Researchers observe those behaviors in small systems, such as nanoscale devices (devices about 10-9 meters long). Aaron studies few-centimeter-long devices. Offsetting the devices’ size with cold might coax them into exhibiting quantum behaviors.

The cooling sounds as effortless as teaching a cat to play fetch. Aaron lowers his fridge’s temperature in steps. Each step involves checking for leaks: A mix of two fluids—two types of helium—cools the fridge. One type of helium costs about $800 per liter. Lose too much helium, and you’ve lost your shot at graduating. Each leak requires Aaron to warm the fridge, then re-cool it. He hauled helium and pampered the fridge for ten days, before the temperature reached 10 milliKelvins (0.01 units above absolute zero). He then worked like…well, like a grad student to check for quantum behaviors.

Aaron came to mind at IBM.

“How long does cooling your fridge take?” I asked Nick Bronn.

Nick works at Watson, IBM’s research center in Yorktown Heights, New York. Watson has sweeping architecture frosted with glass and stone. The building reminded me of Fred Astaire: decades-old, yet classy. I found Nick outside the cafeteria, nursing a coffee. He had sandy hair, more piercings than I, and a mandate to build a quantum computer.


IBM Watson

“Might I look around your lab?” I asked.

“Definitely!” Nick fished out an ID badge; grabbed his coffee cup; and whisked me down a wide, window-paneled hall.

Different researchers, across the world, are building quantum computers from different materials. IBMers use superconductors. Superconductors are tiny circuits. They function at low temperatures, so IBM has seven closet-sized fridges. Different teams use different fridges to tackle different challenges to computing.

Nick found a fridge that wasn’t running. He climbed half-inside, pointed at metallic wires and canisters, and explained how they work. I wondered how his cooling process compared to Aaron’s.

“You push a button.” Nick shrugged. “The fridge cools in two days.”

IBM, I learned, has dry fridges. Aaron uses a wet fridge. Dry and wet fridges operate differently, though both require helium. Aaron’s wet fridge vibrates less, jiggling his experiment less. Jiggling relates to transferring heat. Heat suppresses the quantum behaviors Aaron hopes to observe.

Heat and warmth manifest in many ways, in physics. Count Rumford, an 18th-century American-Brit, conjectured the relationship between heat and jiggling. He noticed that drilling holes into canons immersed in water boils the water. The drill bits rotated–moved in circles–transferring energy of movement to the canons, which heated up. Heat enraptures me because it relates to entropy, a measure of disorderliness and ignorance. The flow of heat helps explain why time flows in just one direction.

A physicist friend of mine writes papers, he says, when catalyzed by “blinding rage.” He reads a paper by someone else, whose misunderstandings anger him. His wrath boils over into a research project.

Warmth manifests as the welcoming of a visitor into one’s lab. Nick didn’t know me from Fred Astaire, but he gave me the benefit of the doubt. He let me pepper him with questions and invited more questions.

Warmth manifests as a 500-word disquisition on fridges. I asked Aaron, via email, about how his cooling compares to IBM’s. I expected two sentences and a link to Wikipedia, since Aaron works 12-hour shifts. But he took pity on his theorist friend. He also warmed to his subject. Can’t you sense the zeal in “Helium is the only substance in the world that will naturally isotopically separate (neat!)”? No knowledge of isotopic separation required.

Many quantum scientists like it cold. But understanding, curiosity, and teamwork fire us up. Anyone under the sway of those elements of science likes it hot.

With thanks to Aaron and Nick. Thanks also to John Smolin and IBM Watson’s quantum-computing-theory team for their hospitality.

1In many situations. Some systems, like small magnets, can access negative temperatures.

Life, cellular automata, and mentoring

One night last July, IQIM postdoc Ning Bao emailed me a photo. He’d found a soda can that read, “Share a Coke with Patrick.”

Ning and I were co-mentoring two Summer Undergraduate Research Fellows, or SURFers. One mentee received Ning’s photo: Caltech physics major Patrick Rall.

“Haha,” Patrick emailed back. “I’ll share a Coke.”

Patrick, Ning, and I shared the intellectual equivalent of a six-pack last summer. We shared papers, meals, frustrations, hopes, late-night emails (from Patrick and Ning), 7-AM emails (from me), and webcomic strips. Now a senior, Patrick is co-authoring a paper about his SURF project.

The project grew from the question “What would happen if we quantized Conway’s Game of Life?” (For readers unfamiliar with the game, I’ll explain below.) Lessons we learned about the Game of Life overlapped with lessons I learned about life, as a first-time mentor. The soda fountain of topics contained the following flavors.

Patrick + Coke

Update rules: Till last spring, I’d been burrowing into two models for out-of-equilibrium physics. PhD students burrow as no prairie dogs can. But, given five years in Caltech’s grassland, I wanted to explore. I wanted an update.

Ning and I had trespassed upon quantum game theory months earlier. Consider a nonquantum game, such as the Prisoner’s Dilemma or an election. Suppose that players have physical systems, such as photons (particles of light), that occupy superposed or entangled states. These quantum resources can change the landscape of the game’s possible outcomes. These changes clarify how we can harness quantum mechanics to process, transmit, and secure information.

How might quantum resources change Conway’s Game of Life, or GoL? British mathematician John Conway invented the game in 1970. Imagine a square board divided into smaller squares, or cells. On each cell sits a white or a black tile. Black represents a living organism; white represents a lack thereof.

Conway modeled population dynamics with an update rule. If prairie dogs overpopulate a field, some die from overcrowding. If a black cell borders more than three black neighbors, a white tile replaces the black. If separated from its pack, a prairie dog dies from isolation. If a black tile borders too few black neighbors, we exchange the black for a white. Mathematics columnist Martin Gardner detailed the rest of Conway’s update rule in this 1970 article.

Updating the board repeatedly evolves the population. Black and white shapes might flicker and undulate. Space-ship-like shapes can glide across the board. A simple update rule can generate complex outcomes—including, I found, frustrations, hopes, responsibility for another human’s contentment, and more meetings than I’d realized could fit in one summer.

Prairie dogs

Modeled by Conway’s Game of Life. And by PhD students.

Initial conditions: The evolution depends on the initial state, on how you distribute white and black tiles when preparing the board. Imagine choosing the initial state randomly from all the possibilities. White likely mingles with about as much black. The random initial condition might not generate eye-catchers such as gliders. The board might fade to, and remain, one color.*

Enthusiasm can fade as research drags onward. Project Quantum GoL has continued gliding due to its initial condition: The spring afternoon on which Ning, Patrick, and I observed the firmness of each other’s handshakes; Patrick walked Ning and me through a CV that could have intimidated a postdoc; and everyone tried to soothe everyone else’s nerves but occasionally avoided eye contact.

I don’t mean that awkwardness sustained the project. The awkwardness faded, as exclamation points and smiley faces crept into our emails. I mean that Ning and I had the fortune to entice Patrick. We signed up a bundle of enthusiasm, creativity, programming skills, and determination. That determination perpetuated the project through the summer and beyond. Initial conditions can determine a system’s evolution.

Long-distance correlations:  “Sure, I’d love to have dinner with you both! Thank you for the invitation!”

Lincoln Carr, a Colorado School of Mines professor, visited in June. Lincoln’s group, I’d heard, was exploring quantum GoLs.** He studies entanglement (quantum correlations) in many-particle systems. When I reached out, Lincoln welcomed our SURF group to collaborate.

I relished coordinating his visit with the mentees. How many SURFers could say that a professor had visited for his or her sake? When I invited Patrick to dinner with Lincoln, Patrick lit up like a sunrise over grasslands.

Our SURF group began skyping with Mines every Wednesday. We brainstorm, analyze, trade code, and kvetch with Mines student Logan Hillberry and colleagues. They offer insights about condensed matter; Patrick, about data processing and efficiency; I, about entanglement theory; and Ning, about entropy and time evolution.

We’ve learned together about long-range entanglement, about correlations between far-apart quantum systems. Thank goodness for skype and email that correlate far-apart research groups. Everyone would have learned less alone.


Long-distance correlations between quantum states and between research groups

Time evolution: Logan and Patrick simulated quantum systems inspired by Conway’s GoL. Each researcher coded a simulation, or mathematical model, of a quantum system. They agreed on a nonquantum update rule; Logan quantized it in one way (constructed one quantum analog of the rule); and Patrick quantized the rule another way. They chose initial conditions, let their systems evolve, and waited.

In July, I noticed that Patrick brought a hand-sized green spiral notepad to meetings. He would synopsize his progress, and brainstorm questions, on the notepad before arriving. He jotted suggestions as we talked.

The notepad began guiding meetings in July. Patrick now steers discussions, ticking items off his agenda. The agenda I’ve typed remains minimized on my laptop till he finishes. My agenda contains few points absent from his, and his contains points not in mine.

Patrick and Logan are comparing their results. Behaviors of their simulations, they’ve found, depend on how they quantized their update rule. One might expect the update rule to determine a system’s evolution. One might expect the SURF program’s template to determine how research and mentoring skills evolve. But how we implement update rules matters.

SURF photo

Caltech’s 2015 quantum-information-theory Summer Undergraduate Research Fellows and mentors

Life: I’ve learned, during the past six months, about Conway’s Game of Life, simulations, and many-body entanglement. I’ve learned how to suggest references and experts when I can’t answer a question. I’ve learned that editing SURF reports by hand costs me less time than editing electronically. I’ve learned where Patrick and his family vacation, that he’s studying Chinese, and how undergrads regard on-campus dining. Conway’s Game of Life has expanded this prairie dog’s view of the grassland more than expected.

I’ll drink a Coke to that.

Glossary: Conway’s GoL is a cellular automatonA cellular automaton consists of a board whose tiles change according to some update rule. Different cellular automata correspond to different board shapes, to boards of different dimensions, to different types of tiles, and to different update rules.

*Reversible cellular automata have greater probabilities (than the GoL has) of updating random initial states through dull-looking evolutions.

**Others have pondered quantum variations on Conway’s GoL.