Reading the sub(linear) text

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 batteriesthe concentration of entanglementthe 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 + an, 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”

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.

Hooke image copy

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).

Vahala image copy

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.

The return of the superconducting high school teacher

Last summer, I was blessed with the opportunity to learn about the basics of high temperature superconductors in the Yeh Group under the tutelage of visiting Professor Feng. We formed superconducting samples using a process known as Pulse Laser Deposition. We began testing the properties of the samples using X-Ray Diffraction, AC Susceptibility, and SQUIDs (superconducting quantum interference devices). I brought my new-found knowledge of these laboratory techniques and processes back into the classroom during this past school year. I was able to answer questions about the formation, research, and applications of superconductors that I had been unable to address prior to this valuable experience.

This summer I returned to the IQIM Summer Research Institute to continue my exploration of superconductors and gain even deeper research experience. This time around I have accompanied Caltech second year graduate student Kyle Chen in testing samples using the Scanning Tunneling Microscope (STM), some of which I helped form using Pulse Laser Deposition with Professor Feng last summer. I have always been curious about how we can have atomic resolution. This has been my big chance to have hands-on experience working with STM that makes it possible!

The Scanning Tunneling Microscope was invented by the late Heinrich Rohrer and Gerd Binnig at IBM Research in Zurich, Switzerland in 1981. STM is able to scan the surface contours of substances using a sharp conductive tip. The electron tunneling current through the tip of the microscope is exponentially dependent on the distance (few Angstroms) to the substance surface. The changing currents at different locations can then be compiled to produce three dimensional images of the topography of the surface on the nano-scale. Or conversely the distance can be measured while the current is held constant. STM has a much higher resolution of images and avoids the problems of diffraction and spherical aberration from lenses. This level of control and precision through STM has enabled scientists to use tools with nanometer precision, allowing scientists even to manipulate atoms and their bonds. STM has been instrumental in forming the field of nanotechnology and the modern study of DNA, semiconductors, graphene, topological insulators, and much more! Just five years after building their first STM, Rohrer and Binning’s work rightfully earned them the 1986 Nobel Prize in Physics.

Descending into the Sloan basement, Kyle and I work to prepare and scan several high temperature superconducting (HTSC) Calcium Doped YBCO (\rm Y_{1-x} Ca_x Ba_2 Cu_3 O_{7-\delta}) samples in order better to understand the pairing mechanism that causes Cooper Pairs for superconductivity. In regular metals, the pairing mechanism via phonon lattice vibrations is fairly well understood by physicists. Meanwhile, the pairing mechanism for HTSC is still a mystery. We are also investigating how this pairing changes with doping, as well as how the magnetic field is channeled up vortices within HTSC.

One of our first tasks is to make probe tips for STM. Adding Calcium Chloride to de-ionized water, we are preparing a liquid conductive path to begin the chemical etching of the probe tip. Using a 10V battery, a wire bent into a ring is connected to the battery and placed in the Calcium Chloride solution. Then a thin platinum iridium wire, also connected to the voltage source, is placed at the center of the conductive ring. The circuit is complete and a current of about half an Ampere is used to erode uniformly the outer surface of the platinum iridium wire, forming a sharp tip. We examine the tip under a traditional microscope to scrutinize our work. Ideally, the tip is only one atom thick! If not, we are charged with re-etching until we reach a more suitable straight, uniform, sharp tip.   As we work to prepare the platinum iridium tips, a stoic picture of Neils Bohr looks down at our work with the appropriate adjacent quotation, ” When it comes to atoms, language can be used only as in poetry.  The poet, too, is not nearly so concerned with describing facts as with creating images. ”  After making two or three nearly perfect tips, we clean and store them in the tip case and proceed to the next step of preparation.

We are now ready to clean the sample to be tested. Bromine etching removes any oxidation or impurities that have formed on our sample, leaving a top bromine film layer. We remove the bromine-residue layer with ethanol and then plunge further into the (sub)basement to load the sample into the STM casing before oxidation begins again. The STM in the Yeh Lab was built by Professor Nai-Chang Yeh and her students eleven years ago. There are multiple layers of vacuum chambers and separate dewars, each with its own meticulous series of steps to prepare for STM testing. At the center is a long, central STM tube. Surrounding this is a large cylindrical dewar. On the perimeter is an exterior large vacuum chamber.

First we must load the newly etched YBCO sample and tip into the central STM tube. The inner tube currently lays across a work bench beneath desk lamps. We must transfer the tiny tip from the tip case to just above the sample. While loading the tip with an equally minuscule flathead screwdriver, it became quite clear to me that I could never be a surgeon! The superconducting sample is secured in place with a small cover plate and screw. A series of electronic tests for resistance and capacitance must be conducted to confirm that there are no shorts in the numerous circuits. Next we must vacuum pump the inner cylindrical tube holding the sample, tip, and circuitry until the pressure is 10^{-4} Bar. Then we “bake” the inner chamber, using a heater to expel any other gas, while the vacuum pump continues until we reach approximately 10^{-5} Bar. The heater is turned off and the vacuum continues to pump until we reach 10^{-6} Bar. This entire vacuum process takes approximately 15 hours…

During this span of time, I have the opportunity to observe the dark, cold STM room. The door, walls and ceiling are covered with black rubber and spongy padding to absorb vibration. The STM room is in the lowest level basement for the same reason. The vibration from human steps near the testing generates noise in the data, so every precaution is made to minimize noise. Giant cement blocks lay across the STM metal box to increase inertia and decrease noise. I ask Kyle what he usually does with this “down” time. We discuss the importance of reading equipment manuals to grasp a better understanding of the myriad of tools in the lab. He says he needs to continue reading the papers published by the Yeh Lab Group. In knowing what questions your research group has previously answered, one has a better understanding of the history and the direction of current work.

The next day, the vacuum-pumped inner chamber is loaded to the center of the STM dewar. We flush the surrounding chambers with nitrogen gas to extricate any moisture or impurities that may have entered since our last testing. Next we can set up the equipment for a liquid nitrogen transfer which lasts approximately 2 hours, depending on the transfer rate. As the liquid nitrogen is added to the system, we meticulously monitor the temperature of the STM system. It must reach 80 Kelvin before we again test the electronics. Eventually it is time to add the liquid helium. Since liquid helium is quite expensive, additional precautions are taken to ensure maximum efficiency for helium use. It is beautiful to watch the moisture in the air deposit in frost along the tubing connecting the nitrogen and helium tanks to the STM dewar. The stillness of the quiet basement as we wait for the transfer is calming. Again, we carefully monitor the temperature drop as it eventually reaches 4.2 Kelvin. For this research, STM must be cooled to this temperature because we must drop below the critical temperature of the sample in order to observe superconductivity. The lower the temperature, the more of the superconducting component manifests itself. Hence the spectrum will have higher resolution. Liquid nitrogen is first added because it can carry over 90% of the heat away due to its higher mass. Nitrogen is also significantly cheaper than liquid helium. The liquid helium is added later, because it is even cooler than liquid nitrogen.

After adding additional layers of rubber padding on top of the closed STM, we can move over to the computer that controls the STM tip. It takes approximately one hour for the tip to be slowly lowered within range for a tunneling current. Kyle examines the data from the approach to the surface. If all seems normal, we can begin the actual scan of the sample!
An important part of the lab work is trouble shooting. I have listed the ideal order of steps, but as with life, things do not always proceed as expected. I have grown in awe of the perseverance and ingenuity required for daily troubleshooting. The need to be meticulous in order to avoid error is astonishing. I love that some common household items can be a valuable tool in the lab. For example, copper scrubbers used in the kitchen serve as a simple conducting path around the inner STM chamber. Floss can be used to tie down the most delicate thin wires. I certainly have grown in my immense respect for the patience and brilliance required in real research.

I find irony in the quiet simplicity of recording and analyzing data, the stillness of carefully transferring liquid helium juxtaposed to the immense complexity and importance of this groundbreaking research. I appreciate the moments of simple quiet in the STM room, the fast paced group meetings where everyone chimes in on their progress, or the boisterous collaborative brainstorming to troubleshoot a new problem. The summer weeks in the Sloan basement have been a welcome retreat from the exciting, transformative, and exhausting year in the classroom. I am grateful for the opportunity to learn more about superconductors, quantum tunneling, vacuum pumps, sonicators, lab safety, and more. While I will not be bromine etching, chemically forming STM tips, or doing liquid helium transfers come September, I have a new-found love for the process of research that I will radiate to my students.

High School Physics Teacher Embedded on A Quest to Squash Quantum Noise

Date: 8/22/2013

Location: Caltech Cryo Lab, West Bridge:

Hello: I am Steve Maloney, a Physics and Chemistry teacher intern from Duarte High School, sponsored by IQIM (Institute for Quantum Information and Matter), doing whatever I can to be of assistance to Dr. Nicolas Smith-Lefebvre. Upon meeting him in mid-June I soon learned that our mission for the length of my visit was to assist him in determining with a greater degree of certainty the linear expansion coefficient of silicon in and around 125 K. (See below)

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Fig. 1: Silicon cavity.

The temperature of 125 K is of special interest to operators of LIGO (Laser Interferometer Gravitational Wave Observatory), because that is one of two temperatures where the thermal expansion coefficient, \alpha, of silicon is equal to zero. A zero linear expansion coefficient is of special interest to LIGO researchers because a small change in temperature inside the cryostat, (see Fig. 2, below) will not result in a significant change in length for the silicon cavity shown in Fig. 1.

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Fig. 2: Inside the Cryostat

Scientists working at LIGO need to know with great precision the length of the resonance cavity, because as gravitational waves pass through the cavity, they simultaneously compress the length of the cavity and stretch in a direction perpendicular to the shortening (warp). The arrival of a gravity wave produces a signal in the Fabry-Perot Interferometer, shown in Fig. 3, below.

Fig. 3: LIGO set-up with Fabry-Perot cavity.

Fig. 3: LIGO set-up with Fabry-Perot cavity.

Because the interferometer is sensitive to changes in length of as little as 1X10-15 m, sources of noise must be reduced to an absolute minimum. This brings us back to establishing the Thermal Coefficient of Linear Expansion, \alpha. Knowing the value of \alpha to a greater certainty will provide LIGO researchers the mathematical tools to better correct for small changes in temperature for the cavity, thus reducing the noise, therefore increasing the sensitivity of the Gravity Wave Detector.

So Where Do I Fit In?

In the Cryo-Lab on Thursday, July 11 2013, Nicolas Smith-Lefebvre, with my assistance, fed a radio frequency of 160.13 Mhz by means of a frequency-to-voltage transducer. The frequency fed into the transducer was changed by a fixed amount, and the change in voltage was noted. The hz / volt constant obtained was 253.9 hz / mvolt.

Nicolas then locked the east-west cryo-cavities so that the beat signal was approximately 0 (zero) volts.  See the plot, below:

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We then sent a 3.16 second pulse (approximated) of a 3.6 mWatt, 532 nm laser, (green) onto the surface of a mirror that reflects in the infrared, but absorbs in visible wavelengths. (Note top graph) I manufactured the electrical power interface for the laser by modifying the casing of a BIC disposable pen. The mirror was situated at the aperture of a silicon spacer.

The goal of the experiment was to determine the absorbance of the silicon mirror of the 532 nm laser.

Assuming we know the quantity of energy pulsed into the mirror:

3.6 mWatt * 3.16 s = .011376 joules,

the change in length of the cavity was determined by: Change in f/f1550nm = change in L/ L0

The change in volts (.025) gave us a change in f of 6.3475 x 103 hz.

With L0 having a value of 10 cm, that means change in L was 3.2794 x 10-10cm.

The specific heat capacity of Si is 700j/k*kg.

Coefficient of linear expansion for Si = 2.6 x 10 -6/K.

To calculate increase in temperature we need to obtain the change in L.

If 2.6 x 10 -6/C  x 10 cm x DT = DL = 3.2794 x 10-10 cm, then DT must be 1.2613 x 10 -5 K.

If DT = 1.2613 x 10-5 K , then Q must equal .41 kg x 700 j/kg Kx1.2613 x 10-5 K = 3.6 x10-3 j,

Q/Epulse=  3.6 x 10-3j / 1.1376 x 10-2j = .316 absorbance.

In other words, the silicon cavity reflected about 68% of the light that struck it.

What have I come away with from this experience?

What struck me first and foremost during this summer internship in the Cryo-Lab was the importance of future knowledge workers of having certain key skills. Among them:

Proficiency in Language

Proficiency in Math

Proficiency in Science

Proficiency in Coding

I will share my insights with my local school district and I intend to capitalize on the connections I made during my experience at Caltech.

Acknowledgements:

I would like to thank the Duarte Unified School District for giving me a leave of absence, Rana Adhikari for, yet again, finding space for me in spite of my general ineptitude regarding General Relativity, Spyridon Michalakis (Spiros) for inviting me back and letting me participate in cutting-edge science, and most of all I would like to thank Nicolas Smith-Lefebvre (softball savant),  and David Yeaton-Massey (D-Mass), for their patience, generosity, and mentoring.

 

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Tsar Nikita and His Scientists

Once upon a time, a Russian tsar named Nikita had forty daughters:

                Every one from top to toe
                Was a captivating creature,
                Perfect—but for one lost feature.

 
So wrote Alexander Pushkin, the 19th-century Shakespeare who revolutionized Russian literature. In a rhyme, Pushkin imagined forty princesses born without “that bit” “[b]etween their legs.” A courier scours the countryside for a witch who can help. By summoning the devil in the woods, she conjures what the princesses lack into a casket. The tsar parcels out the casket’s contents, and everyone rejoices.

“[N]onsense,” Pushkin calls the tale in its penultimate line. A “joke.”

The joke has, nearly two centuries later, become reality. Researchers have grown vaginas in a lab and implanted them into teenage girls. Thanks to a genetic defect, the girls suffered from Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome: Their vaginas and uteruses had failed to grow to maturity or at all. A team at Wake Forest and in Mexico City took samples of the girls’ cells, grew more cells, and combined their harvest with vagina-shaped scaffolds. Early in the 2000s, surgeons implanted the artificial organs into the girls. The patients, the researchers reported in the journal The Lancet last week, function normally.

I don’t usually write about reproductive machinery. But the implants’ resonance with “Tsar Nikita” floored me. Scientists have implanted much of Pushkin’s plot into labs. The sexually deficient girls, the craftsperson, the replacement organs—all appear in “Tsar Nikita” as in The Lancet. In poetry as in science fiction, we read the future.

Though threads of Pushkin’s plot survive, society’s view of the specialist has progressed. “Deep [in] the dark woods” lives Pushkin’s witch. Upon summoning the devil, she locks her cure in a casket. Today’s vagina-implanters star in headlines. The Wall Street Journal highlighted the implants in its front section. Unless the patients’ health degrades, the researchers will likely list last week’s paper high on their CVs and websites.

http://news.wfu.edu/2011/05/31/research-park-updates-to-be-presented/, http://www.orderwhitemoon.org/goddess/babayaga/BabaYaga.html

Much as Dr. Atlántida Raya-Rivera, the paper’s lead author, differs from Pushkin’s witch, the visage of Pushkin’s magic wears the nose and eyebrows of science. When tsars or millenials need medical help, they seek knowledge-keepers: specialists, a fringe of society. Before summoning the devil, the witch “[l]ocked her door . . . Three days passed.” I hide away to calculate and study (though days alone might render me more like the protagonist in another Russian story, Chekhov’s “The Bet”). Just as the witch “stocked up coal,” some students stockpile Red Bull before hitting the library. Some habits, like the archetype of the wise woman, refuse to die.

From a Russian rhyme, the bones of “Tsar Nikita” have evolved into cutting-edge science. Pushkin and the implants highlight how attitudes toward knowledge have changed, offering a lens onto science in culture and onto science culture. No wonder readers call Pushkin “timeless.”

But what would he have rhymed with “Mayer-Rokitansky-Küster-Hauser”?

 

 

 

“Tsar Nikita” has many nuances—messages about censorship, for example—that I didn’t discuss. To the intrigued, I recommend The Queen of Spades: And selected works, translated by Anthony Briggs and published by Pushkin Press.

 

Summer of Science: Caltech InnoWorks 2013

The following post is a collaboration between visiting undergraduates Evan Giarta from Stanford University and Joy Hui from Harvard University. As mentors for the 2013 Caltech InnoWorks Academy, Evan and Joy agreed to share their experience with the audience of this blog.

Innoworks-68All throughout modern history, science and mathematics have been the foundation for engineering new, world-advancing technologies. From the wheel and sailboat to the automobile and jumbo jet, the fields of science, technology, engineering and math (STEM) have helped our world and its people move faster, farther, and forward. Now, more than ever, products that were unimaginable a century ago are used every day in households and businesses all over the earth, products made possible by generations of scientists, mathematicians, engineers and technologists.

There is, however, some troublesome news regarding the state of our nation’s math and science education. For the past few years, education and news reports have ranked the United States behind other developed countries in science and mathematics. In fact, the proportion of students that score in the most advanced levels of math and science in the United States is significantly lower than that of several other nations. This reality brings to light a stark concern: If proficiency in science and math is necessary for the engineering of novel technologies and breakthrough discoveries, but is something the next generation will lack, what will become of the production industry, our economy, and global security? While the answer to this question might range from complete and utter chaos to little or no effect, it seems reasonable to try and avoid finding out. Rather, we–the community of collective scientists, technologists, engineers, mathematicians–should seek to solve this problem: What can we do to restore the integrity and substance of the educational system, especially in science and math?

Innoworks-36Although there is no easy answer to this question, there are ongoing efforts to address this important issue, one of which is the InnoWorks Academy. Founded in 2003 by a group of Duke undergraduates, the United InnoWorks Academy has developed summer programs that encourage underprivileged middle school students to explore the fields of science, technology, engineering, math, and medicine, (STEM^2) free of charge. The academy is sponsored by a variety of businesses and organizations, including GlaxoSmithKline, Cisco, Project Performance Corporation, Do Something, St. Andrew’s School, University of Pennsylvania, University of California, Los Angeles, and many others. InnoWorks Academy was a winner of the 2007 BRICK Awards and received both the MIT Global Community Choice Award and the MIT IDEAS Challenge Grand Prize in 2011. In ten short years, the United InnoWorks Academy has successfully conducted over 50 summer programs for more than 2,000 students through the contributions of over 1,000 volunteers. Currently, InnoWorks has chapters at about a dozen universities and is scheduled to add three more chapters this coming summer.

Innoworks-34In early August of 2013, the Caltech InnoWorks chapter hosted its second annual summer camp, and Joy and I (Evan) were privileged to be invited as program mentors. As people on the inside, we got a first hand look at how the organization prepares and runs the week-long event and what the students themselves experience in the hands-on, interactive and collaborative one-of-a-kind opportunity that is InnoWorks.

Since Joy and I kept a diary of each day’s activities, we thought you may like to see what our middle-schoolers experienced during that week. Here is a play-by-play of the first few days from Joy’s perspective.

Monday, August 5, 2013 was the first day of our camp! Before I go on with talking about the cool things we did that day, I’d like to introduce my team. The self-titled YOLOSWAG consisted of Michael, Chase, Evan, Phaelan and myself. Michael was the oldest, and a little shy at first, but he definitely started talking when he got comfortable. Chase was respectful and polite, and we hit it off immediately. Evan loved science and had lots of questions and knew a TON. Phaelan was the only other girl on the team, but she was very nice and friendly to the other students, and eager to help with anything she could. We all seem different, right? But wait, here’s the best part: we were all die-hard Percy Jackson (property of Rick Riordan) fans! We were definitely the best team.

Innoworks-24

Anyway, back to the actual stuff we did. One of the first things we saw was a cloud demo, essentially the creation of a cloud in a fish tank, with lots of dry ice and water. The demonstrator, Rob Usiskin, stuck a lot of dry ice in the (empty) fish tank, and poured some water into the tank, which caused the water to turn into a fog, which turns out to be the exact form of a cloud! Add a bubble maker, a question of whether bubbles will float or sink on the cloud, and a room full of InnoWorks campers (about 40 of them), and you will get an hour of general excitement. See the pictures for yourself! (The bubbles, float, by the way, even when the cloud is invisible!)

Innoworks-32

Following the demonstration, we made Soap Boats. We were apparently supposed to cut index cards into the shape of boats, and dab a little bit of soap on the bottom of the boat, and set the boat in the water. These “Soap Boats” were supposed to be propelled forward by the soap’s ability to decrease the surface tension of the water it touched. Ours, appropriately named “Titanic,” however, simply sat in the water until the water soaked through, and the Titanic sank for the second time in history. Many other teams’ boats fared about the same, but we certainly had a blast designing and naming our Soap Boat!

The last activity of the day was a secret message decoded with bio-luminescence. Each team was given a vial of dried up ostracods, which are sea creatures found glowing in the darkness of the deep sea. Then, each team crushed the ostracods and mixed the resulting powder with water to catalyze the bio-luminescence. Every mentor had written a secret message on a slip of paper, folded it, and handed it to their teams to decipher in the dark (Mine said: YOLOSWAG for the win). The convenient cleaning closet provided said darkness–Spiros, our faculty mentor, suggested that it might also provide passage to Narnia. I don’t think we lost any of our students that day, so no Narnia-traveling was done; by students. Nevertheless, it was a fun-filled and action-packed day, and a great start to an eventful week.

Tuesday was full of fun, hands-on activities. After a short lesson on the effects of air resistance and gravity on free-falling objects, we demonstrated the concept with a thin sheet of paper and a large textbook. As expected, when placed side by side and dropped, air resistance caused the sheet of paper to hit the ground much later than the textbook. But when the sheet of paper was placed directly above the textbook, to the shock of students, both items fell at the exact same rate. Though thorough in their knowledge of physical laws, the connection between their conceptual understanding and real life application had yet to be established. And as a result, when asked to explain what happened and why, the best answer one could muster was simply, “SCIENCE!”.

Following an exercise consisting of blow dryers and floating ping pong balls, the kids received a brief tutorial on how tornadoes are formed by air moving through high and low pressure regions and gusts of vertically rising winds. Due to the forces it is producing and acting upon, the tornado would then be able to more or less sustain itself. To explore this concept further, students constructed water tornado machines by taping two soda bottles together at their openings. Laughter and wetness ensued. Some groups added small trinkets in their tornado machine to observed the water tornado’s effect on “debris”. One team in particular inserted duct tape sharks, and aptly renamed themselves as Sharknado.

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In the afternoon, the campers were presented a lesson on the transportation of sailboats and aircraft. Contrary to what most people intuit, the fastest way to control a boat is not to flow in the direction of the wind, but to place the sail at the heading which produces a net force, which can be explained by Bernoulli’s Principle. It states that faster moving fluid has less pressure than slower moving fluid, therefore producing a force from the slower moving side to the faster moving side. Though in sailing this force is initially barely noticeable, over time it creates a large impulse to move the craft at considerable speeds. The same principle can also explain the way a plane takes flight.

With the importance of good design in mind, students were tasked with prototyping the fastest water-bottle boat. Given a solar panel, electric motor, various propellers, empty bottle, tape, and other construction essentials, kids started with basic designs, then diversified in order to gain an edge against other teams. Some teams boasted two-bottle designs, and others used one, each type having trade-offs in speed and stability. Few implemented style upgrades with graphics and colors, and even fewer leveraged performance modifications with ballast and crude control systems. But with a tough deadline to meet, not all boats met their intended specifications. Nonetheless, the races commenced and each team’s innovation was tested in the torrents of Caltech’s Beckman Fountain. Some failed, but those that survived were rewarded accordingly.

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By the end of the second day, many of the campers’ initial shyness had been replaced with conversation and budding new friendships. Lunch hour and break times allowed time for kids and mentors alike to hang out and enjoy themselves in California’s summer sun in-between discovering the applications of science and math to engineering, medicine, and technology. These moments of discovery, no matter how rare, are the reasons why we do what we do as we continue our research, studies, and work to improve the world we live in.

Guns versus butter in quantum information

From my college’s computer-science club, I received a T-shirt that reads:

while(not_dead){

sleep--;

time--;

awesome++;

}

/*There’s a reason we can’t hang out with you…*/

The message is written in Java, a programming language. Even if you’ve never programmed, you likely catch the drift: CS majors are the bees’ knees because, at the expense of sleep and social lives, they code. I disagree with part of said drift: CS majors hung out with me despite being awesome.

photo-3 copy

The rest of the drift—you have to give some to get some—synopsizes the physics I encountered this fall. To understand tradeoffs, you needn’t study QI. But what trades off with what, according to QI, can surprise us.

The T-shirt haunted me at the University of Nottingham, where researchers are blending QI with Einstein’s theory of relativity. Relativity describes accelerations, gravity, and space-time’s curvature. In other sources, you can read about physicists’ attempts to unify relativity and quantum mechanics, the Romeo and Tybalt of modern physics, into a theory of quantum gravity. In this article, relativity tangos with quantum mechanics in relativistic quantum information (RQI). If I move my quantum computer, RQIers ask, how do I change its information processing? How does space-time’s curvature affect computation? How can motion affect measurements?

Answers to these questions involve tradeoffs.

Nottingham

Nottingham researchers kindly tolerating a seminar by me

For example, acceleration entangles particles. Decades ago, physicists learned that acceleration creates particles. Say you’re gazing into a vacuum—not empty space, but nearly empty space, the lowest-energy system that can exist. Zooming away on a rocket, I accelerate relative to you. From my perspective, more particles than you think—and higher-energy particles—surround us.

Have I created matter? Have I violated the Principle of Conservation of Energy (and Mass)? I created particles in a sense, but at the expense of rocket fuel. You have to give some to get some:

Fuel--;
Particles++;

The math that describes my particles relates to the math that describes entanglement.* Entanglement is a relationship between quantum systems. Say you entangle two particles, then separate them. If you measure one, you instantaneously affect the other, even if the other occupies another city.

Say we encode information in quantum particles stored in a box.** Just as you encode messages by writing letters, we write messages in the ink of quantum particles. Say the box zooms off on a rocket. Just as acceleration led me to see particles in a vacuum, acceleration entangles the particles in our box. Since entanglement facilitates computation, you can process information by shaking a box. And performing another few steps.

When an RQIer told me so, she might as well have added that space-time has 106 dimensions and the US would win the World Cup. Then my T-shirt came to mind. To get some, you have to give some. When you give something, you might get something. Giving fuel gets you entanglement. To prove that statement, I need to do and interpret math. Till I have time to,

Fuel--;
Entanglement++;

offers intuition.

After cropping up in Nottingham, my T-shirt reared its head (collar?) in physics problem after physics problem. By “consuming entanglement”—forfeiting that ability to affect the particle in another city—you can teleport quantum information.

Entanglement--;
Quantum teleportation++;

My research involves tradeoffs between information and energy. As the Hungarian physicist Leó Szilárd showed, you can exchange information for work. Say you learn which half of a box*** a particle occupies, and you trap the particle in that half. Upon freeing the particle—forfeiting your knowledge about its location—you can lift a weight, charge a battery, or otherwise store energy.

Information--;
Energy++;

If you expend energy, Rolf Landauer showed, you can gain knowledge.

Energy--;
Information++;

No wonder my computer-science friends joked about sleep deprivation. But information can energize. For fuel, I forage in the blending of fields like QI and relativity, and in physical intuitions like those encapsulated in the pseudo-Java above. Much as Szilard’s physics enchants me, I’m glad that the pursuit of physics contradicts his conclusion:

while(not_dead){

Information++;

Energy++;

}

The code includes awesome++ implicitly.

*Bogoliubov transformations, to readers familiar with the term.

**In the fields in a cavity, to readers familiar with the terms.

***Physicists adore boxes, you might have noticed.

With thanks to Ivette Fuentes and the University of Nottingham for their hospitality and for their introduction to RQI.