# 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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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

Imagine swapping peas 1 and 3.

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

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

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.

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.

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.

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.

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.”

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:

3) Hit “Enter.”
4) Kick yourself for entering the wrong password.
6) Hit “Enter.”
7) Open a web browser.
9) Type “anyone lived in a pretty how town e e cummings” into the search bar.
10) Hit “Enter.”
12) Exclaim, “Really? April is National Poetry Month?”
14) Remember that you intended to look up a 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.

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.

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.

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.

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.

# Carbon copy

The anticipatory excitement of summer vacation endures in the teaching profession like no place outside childhood schooldays. Undoubtedly, ranking high on the list that keep teachers teaching. The excitement was high as the summer of 2015 started out the same as it had the three previous years at Caltech. I would show up, find a place to set up, and wait for orders from scientist David Boyd. Upon arrival in Dr. Yeh’s lab, surprisingly, I found all the equipment and my work space very much untouched from last year. I was happy to find it this way, because it likely meant I could continue exactly where I left off last summer. Later, I realized David’s time since I left was devoted to the development of a revolutionary new process for making graphene in large sheets at low temperatures. He did not have time to mess with my stuff, including the stepper-motor I had been working on last summer.

So, I place my glorified man purse in a bottom drawer, log into my computer, and wait.   After maybe a half hour I hear the footsteps set to a rhythm defined only by someone with purpose, and I’m sure it’s David.  He peeks in the little office where I’m seated and with a brief welcoming phrase informs me that the goal for the summer is to wrap graphene around a thin copper wire using, what he refers to as, “your motor.” The motor is a stepper motor from an experiment David ran several years back. I wired and set up the track and motor last year for a proposed experiment that was never realized involving the growth of graphene strips. Due to the limited time I spend each summer at Caltech (8 weeks), that experiment came to a halt when I left, and was to be continued this year. Instead, the focus veered from growing graphene strips to growing a two to three layer coating of graphene around a copper wire. The procedure remains the same, however, the substrate onto which the graphene grows changes. When growing graphene-strips the substrate is a 25 micron thick copper foil, and after growth the graphene needs to be removed from the copper substrate. In our experiment we used a copper wire with an average thickness of 154 microns, and since the goal is to acquire a copper wire with graphene wrapped around, there’s no need to remove the graphene.

Noteworthy of mention is the great effort toward research concerning the removal and transfer of graphene from copper to more useful substrates. After graphene growth, the challenge shifts to separating the graphene sheet from the copper substrate without damaging the graphene. Next, the graphene is transferred to various substrates for fabrication and other purposes. Current techniques to remove graphene from copper often damage the graphene, ill-effecting the amazing electrical properties warranting great attention from R&D groups globally. A surprisingly simple new technique employs water to harmlessly remove graphene from copper. This technique has been shown to be effective on plasma-enhanced chemical vapor deposition (PECVD).  PECVD is the technique employed by scientist David Boyd, and is the focus of his paper published in Nature Communications in March of 2015.

So, David wants me to do something that has never been done before; grow graphene around a copper wire using a translation stage. The technique is to attach an Evenson cavity to the stage of a stepper motor/threaded rod apparatus, and very slowly move the plasma along a strip of copper wire. If successful, this could have far reaching implications for use with copper wire including, but certainly not limited to, corrosion prevention and thermal dissipation due to the high thermal conductivity exhibited by graphene. With David granting me free reign in his lab, and Ph.D. candidate Chen-Chih Hsu agreeing to help, I felt I had all the tools to give it a go.

Setting up this experiment is similar to growing graphene on copper foil using PECVD with a couple modifications. First, prior to pumping the quartz tube down to a near vacuum, we place a single copper wire into the tube instead of thin copper foil. Also, special care is taken when setting up the translation stage ensuring the Evenson cavity, attached to the stage, travels perfectly parallel to the quartz tube so as not to create a bind between the cavity and tube during travel. For the first trial we decide to grow along a 5cm long section of copper wire at a translation speed of 25 microns per second, which is a very slow speed made possible by the use of the stepper motor apparatus. Per usual, after growth we check the sample using Raman Spectroscopy. The graph shown here is the actual Raman taken in the lab immediately after growth. As the sample is scanned, the graph develops from right to left.  We’re not expecting to see anything of much interest, however, hope and excitement steadily rise as the computer monitor shows a well defined 2D-peak (right peak), a G-peak (middle peak), and a D-peak (left peak) with a height indicative of high defects.  Not the greatest of Raman spectra if we were shooting for defect-free monolayer graphene, but this is a very strong indication that we have 2-3 layer graphene on the copper wire.  How could this be? Chen-Chih and I looked at each other incredulously.  We quickly checked several locations along the wire and found the same result.  We did it!  Not only did we do it, but we did it on our first try!  OK, now we can party.  Streamers popped up into the air, a DJ with a turn table slid out from one of the walls, a perfectly synchronized kick line of cabaret dancers pranced about…… okay, back to reality, we had a high-five and a back-and-forth “wow, that’s so cool!”

We knew before we even reported our success to David, and eventually Professor Yeh, that they would both, immediately, ask for the exact parameters of the experiment and if the results were reproducible. So, we set off to try and grow again. Unfortunately, the second run did not yield a copper wire coated with graphene. The third trial did not yield graphene, and neither did the fourth or fifth. We were, however, finding that multi-layer graphene was growing at the tips of the copper wire, but not in the middle sections.  Our hypothesis at that point was that the existence of three edges at the tips of the wire aided the growth of graphene, compared to only two edges in the wire’s midsection (we are still not sure if this is the whole story).

In an effort to repeat the experiment and attain the parameters for growth, an issue with the experimental setup needed to be addressed. We lacked control concerning the exact mixture of each gas employed for CVD (Chemical Vapor Deposition). In the initial setup of the experiment, a lack of control was acceptable, because the goal was only to discover if growing graphene around a copper wire was possible. Now that we knew it was possible, attaining reproducible results required a deeper understanding of the process, therefore, more precise control in our setup. Dr. Boyd agreed, and ordered two leak valves, providing greater control over the exact recipe for the mixture of gases used for CVD. With this improved control, the hope is to be able to control and, therefore, detect the exact gas mixture yielding the much needed parameters for reliable graphene growth on a copper wire.

Unfortunately, my last day at Caltech before returning to my regular teaching gig, and the delivery of the leak valves occurred on the same day. Fortunately, I will be returning this summer (2016) to continue the search for the elusive parameters. If we succeed, David Boyd’s and Chen-Chih’s names will, once again, show up in a prestigious journal (Nature, Science, one of those…) and, just maybe, mine will make it there too. For the first time ever.

# Quantum Information: Episode II: The Tools’ Applications

Monday dawns. Headlines report that “Star Wars: Episode VII” has earned more money, during its opening weekend, than I hope to earn in my lifetime. Trading the newspaper for my laptop, I learn that a friend has discovered ThinkGeek’s BB-8 plushie. “I want one!” she exclaims in a Facebook post. “Because BB-8 definitely needs to be hugged.”

BB-8 plays sidekick to Star Wars hero Poe Dameron. The droid has a spherical body covered with metallic panels and lights.Mr. Gadget and Frosty the Snowman could have spawned such offspring. BB-8 has captured viewers’ hearts, and its chirps have captured cell-phone ringtones.

ThinkGeek’s BB-8 plushie

Still, I scratch my head over my friend’s Facebook post. Hugged? Why would she hug…

Oh. Oops.

I’ve mentally verbalized “BB-8” as “BB84.” BB84 denotes an application of quantum theory to cryptography. Cryptographers safeguard information from eavesdroppers and tampering. I’ve been thinking that my friend wants to hug a safety protocol.

Charles Bennett and Gilles Brassard invented BB84 in 1984. Imagine wanting to tell someone a secret. Suppose I wish to coordinate, with a classmate, the purchase of a BB-8 plushie for our friend the droid-hugger. Suppose that the classmate and I can communicate only via a public channel on which the droid-hugger eavesdrops.

Cryptographers advise me to send my classmate a key. A key is a random string of letters, such as CCCAAACCABACA. I’ll encode my message with the string, with which my classmate will decode the message.

I have to transmit the key via the public channel. But the droid-hugger eavesdrops on the public channel. Haven’t we taken one step forward and one step back? Why would the key secure our information?

Because quantum-information science enables me to to transmit the key without the droid-hugger’s obtaining it. I won’t transmit random letters; I’ll transmit quantum states. That is, I’ll transmit physical systems, such as photons (particles of light), whose properties encode quantum information.

A nonquantum letter has a value, such as A or B or C.  Each letter has one and only one value, regardless of whether anyone knows what value the letter has. You can learn the value by measuring (looking at) the letter. We can’t necessarily associate such a value with a quantum state. Imagine my classmate measuring a state I send. Which value the measurement device outputs depends on chance and on how my classmate looks at the state.

If the droid-hugger intercepts and measures the state, she’ll change it. My classmate and I will notice such changes. We’ll scrap our key and repeat the BB84 protocol until the droid-hugger quits eavesdropping.

BB84 launched quantum cryptography, the safeguarding of information with quantum physics. Today’s quantum cryptographers rely on BB84 as you rely, when planning a holiday feast, on a carrot-cake recipe that passed your brother’s taste test on his birthday. Quantum cryptographers construct protocols dependent on lines like “The message sender and receiver are assumed to share a key distributed, e.g., via the BB84 protocol.”

BB84 has become a primitive task, a solved problem whose results we invoke in more-complicated problems. Other quantum-information primitives include (warning: jargon ahead) entanglement distillation, entanglement dilution, quantum data compression, and quantum-state merging. Quantum-information scientists solved many primitive problems during the 1990s and early 2000s. You can apply those primitives, even if you’ve forgotten how to prove them.

A primitive task, like quantum-entanglement distillation

Those primitives appear to darken quantum information’s horizons. The spring before I started my PhD, an older physicist asked me why I was specializing in quantum information theory. Haven’t all the problems been solved? he asked. Isn’t quantum information theory “dead”?

Imagine discovering how to power plasma blades with kyber crystals. Would you declare, “Problem solved” and relegate your blades to the attic? Or would you apply your tool to defending freedom?

Primitive quantum-information tools are unknotting problems throughout physics—in computer science; chemistry; optics (the study of light); thermodynamics (the study of work, heat, and efficiency); and string theory. My advisor has tracked how uses of “entanglement,” a quantum-information term, have swelled in high-energy-physics papers.

A colleague of that older physicist views quantum information theory as a toolkit, a perspective, a lens through which to view science. During the 1700s, the calculus invented by Isaac Newton and Gottfried Leibniz revolutionized physics. Emmy Noether (1882—1935) recast physics in terms of symmetries and conservation laws. (If the forces acting on a system don’t change in time, for example, the system doesn’t gain or lose energy. A constant force is invariant under, or symmetric with respect to, the progression of time. This symmetry implies that the system’s energy is conserved.) We can cast physics instead (jargon ahead) in terms of the minimization of a free energy or an action.

Quantum information theory, this physicist predicted, will revolutionize physics as calculus, symmetries, conservation, and free energy have. Quantum-information tools such as entropies, entanglement, and qubits will bleed into subfields of physics as Lucasfilm has bled into the fanfiction, LEGO, and Halloween-costume markets.

BB84, and the solution of other primitives, have not killed quantum information. They’ve empowered it to spread—thankfully, to this early-career quantum information scientist. Never mind BB-8; I’d rather hug BB84. Perhaps I shall. Engineers have realized technologies that debuted on Star Trek; quantum mechanics has secured key sharing; bakers have crafted cakes shaped like the Internet; and a droid’s popularity rivals R2D2’s. Maybe next Monday will bring a BB84 plushie.

The author hugging the BB84 paper and a plushie. On my wish list: a combination of the two.