The weak shall inherit the quasiprobability.

Justin Dressel’s office could understudy for the archetype of a physicist’s office. A long, rectangular table resembles a lab bench. Atop the table perches a tesla coil. A larger tesla coil perches on Justin’s desk. Rubik’s cubes and other puzzles surround a computer and papers. In front of the desk hangs a whiteboard.

A puzzle filled the whiteboard in August. Justin had written a model for a measurement of a quasiprobability. I introduced quasiprobabilities here last Halloween. Quasiprobabilities are to probabilities as ebooks are to books: Ebooks resemble books but can respond to touchscreen interactions through sounds and animation. Quasiprobabilities resemble probabilities but behave in ways that probabilities don’t.


A tesla coil of Justin Dressel’s


Let p denote the probability that any given physicist keeps a tesla coil in his or her office. p ranges between zero and one. Quasiprobabilities can dip below zero. They can assume nonreal values, dependent on the imaginary number i = \sqrt{-1}. Probabilities describe nonquantum phenomena, like tesla-coil collectors,1 and quantum phenomena, like photons. Quasiprobabilities appear nonclassical.2,3

We can infer the tesla-coil probability by observing many physicists’ offices:

\text{Prob(any given physicist keeps a tesla coil in his/her office)}  =  \frac{ \text{\# physicists who keep tesla coils in their offices} }{ \text{\# physicists} } \, . We can infer quasiprobabilities from weak measurements, Justin explained. You can measure the number of tesla coils in an office by shining light on the office, correlating the light’s state with the tesla-coil number, and capturing the light on photographic paper. The correlation needn’t affect the tesla coils. Observing a quantum state changes the state, by the Uncertainty Principle heralded by Heisenberg.

We could observe a quantum system weakly. We’d correlate our measurement device (the analogue of light) with the quantum state (the analogue of the tesla-coil number) unreliably. Imagining shining a dull light on an office for a brief duration. Shadows would obscure our photo. We’d have trouble inferring the number of tesla coils. But the dull, brief light burst would affect the office less than a strong, long burst would.

Justin explained how to infer a quasiprobability from weak measurements. He’d explained on account of an action that others might regard as weak: I’d asked for help.


Chaos had seized my attention a few weeks earlier. Chaos is a branch of math and physics that involves phenomena we can’t predict, like weather. I had forayed into quantum chaos for reasons I’ll explain in later posts. I was studying a function F(t) that can flag chaos in cold atoms, black holes, and superconductors.

I’d derived a theorem about F(t). The theorem involved a UFO of a mathematical object: a probability amplitude that resembled a probability but could assume nonreal values. I presented the theorem to my research group, which was kind enough to provide feedback.

“Is this amplitude physical?” John Preskill asked. “Can you measure it?”

“I don’t know,” I admitted. “I can tell a story about what it signifies.”

“If you could measure it,” he said, “I might be more excited.”

You needn’t study chaos to predict that private clouds drizzled on me that evening. I was grateful to receive feedback from thinkers I respected, to learn of a weakness in my argument. Still, scientific works are creative works. Creative works carry fragments of their creators. A weakness in my argument felt like a weakness in me. So I took the step that some might regard as weak—by seeking help.



Some problems, one should solve alone. If you wake me at 3 AM and demand that I solve the Schrödinger equation that governs a particle in a box, I should be able to comply (if you comply with my demand for justification for the need to solve the Schrödinger equation at 3 AM).One should struggle far into problems before seeking help.

Some scientists extend this principle into a ban on assistance. Some students avoid asking questions for fear of revealing that they don’t understand. Some boast about passing exams and finishing homework without the need to attend office hours. I call their attitude “scientific machismo.”

I’ve all but lived in office hours. I’ve interrupted lectures with questions every few minutes. I didn’t know if I could measure that probability amplitude. But I knew three people who might know. Twenty-five minutes after I emailed them, Justin replied: “The short answer is yes!”


I visited Justin the following week, at Chapman University’s Institute for Quantum Studies. I sat at his bench-like table, eyeing the nearest tesla coil, as he explained. Justin had recognized my probability amplitude from studies of the Kirkwood-Dirac quasiprobability. Experimentalists infer the Kirkwood-Dirac quasiprobability from weak measurements. We could borrow these experimentalists’ techniques, Justin showed, to measure my probability amplitude.

The borrowing grew into a measurement protocol. The theorem grew into a paper. I plunged into quasiprobabilities and weak measurements, following Justin’s advice. John grew more excited.

The meek might inherit the Earth. But the weak shall measure the quasiprobability.

With gratitude to Justin for sharing his expertise and time; and to Justin, Matt Leifer, and Chapman University’s Institute for Quantum Studies for their hospitality.

Chapman’s community was gracious enough to tolerate a seminar from me about thermal states of quantum systems. You can watch the seminar here.

1Tesla-coil collectors consists of atoms described by quantum theory. But we can describe tesla-coil collectors without quantum theory.

2Readers foreign to quantum theory can interpret “nonclassical” roughly as “quantum.”

3Debate has raged about whether quasiprobabilities govern classical phenomena.

4I should be able also to recite the solutions from memory.

The mechanics of thanksgiving

You and a friend are driving in a car. You’ve almost reached an intersection. The stoplight turns red. 

My teacher had handwritten the narrative on my twelfth-grade physics midterm. Many mechanics problems involve cars: Drivers smash into each other at this angle or that angle, interlocking their vehicles. The Principle of Conservation of Linear Momentum governs how the wreck moves. Students deduce how quickly the wreck skids, and in which direction.

Few mechanics problems involve the second person. I have almost reached an intersection?

You’re late for an event, and stopping would cost you several minutes. What do you do?

We’re probably a few meters from the light, I thought. How quickly are we driving? I could calculate the acceleration needed to—

(a) Speed through the red light.

(b) Hit the brakes. Fume about missing the light while you wait.

(c) Stop in front of the intersection. Chat with your friend, making the most of the situation. Resolve to leave your house earlier next time.

Pencils scritched, and students shifted in their chairs. I looked up from the choices.


Our classroom differed from most high-school physics classrooms. Sure, posters about Einstein and Nobel prizes decorated the walls. Circuit elements congregated in a corner. But they didn’t draw the eye the moment one stepped through the doorway.

A giant yellow smiley face did.

It sat atop the cupboards that faced the door. Next to the smiley stood a placard that read, “Say please and thank you.” Another placard hung above the chalkboard: “Are you showing your good grace and character?”

Our instructor taught mechanics and electromagnetism. He wanted to teach us more. He pronounced the topic in a southern sing-song: “an attitude of gratitude.”

Teenagers populate high-school classrooms. The cynicism in a roomful of teenagers could have rivaled the cynicism in Hemingway’s Paris. Students regarded his digressions as oddities. My high school fostered more manners than most. But a “Can you believe…?” tone accompanied recountings of the detours.

Yet our teacher’s drawl held steady as he read students’ answers to a bonus question on a test (“What are you grateful for?”). He bade us gaze at a box of Wheaties—the breakfast of champions—on whose front hung a mirror. He awarded Symbolic Lollipops for the top grades on tests and for acts of kindness. All with a straight face.

Except, once or twice over the years, I thought I saw his mouth tweak into a smile.

I’ve puzzled out momentum problems since graduating from that physics class. I haven’t puzzled out how to regard the class. As mawkish or moral? Heroic or humorous? I might never answer those questions. But the class led me toward a career in physics, and physicists value data. One datum stands out: I didn’t pack my senior-year high-school physics midterm when moving to Pasadena. But the midterm remains with me.


Good news everyone! Flatland is non-contextual!

Quantum mechanics is weird! Imagine for a second that you want to make an experiment and that the result of your experiment depends on what your colleague is doing in the next room. It would be crazy to live in such a world! This is the world we live in, at least at the quantum scale. The result of an experiment cannot be described in a way that is independent of the context. The neighbor is sticking his nose in our experiment!

Before telling you why quantum mechanics is contextual, let me give you an experiment that admits a simple non-contextual explanation. This story takes place in Flatland, a two-dimensional world inhabited by polygons. Our protagonist is a square who became famous after claiming that he met a sphere.



This square, call him Mr Square for convenience, met a sphere, Miss Sphere. When you live in a planar world like Flatland, this kind of event is not only rare, but it is also quite weird! For people of Flatland, only the intersection of Miss Sphere’s body with the plane is visible. Depending on the position of the sphere, its shape in Flatland will either be a point, a circle, or it could even be empty.


During their trip to flatland, Professor Farnsworth explains to Bender: “If we were in the third dimension looking down, we would be able to see an unhatched chick in it. Just as a chick in a 3-dimensional egg could be seen by an observer in the fourth dimension.’

Not convinced by Miss Sphere’s arguments, Mr Square tried to prove that she cannot exist – Square was a mathematician – and failed miserably. Let’s imagine a more realistic story, a story where spheres cannot speak. In this story, Mr Square will be a physicist, familiar with hidden variable models. Mr Square met a sphere, but a tongue-tied sphere! Confronted with this mysterious event, he did what any other citizen of Flatland would have done. He took a selfie with Miss Sphere. Mr Square was kind enough to let us use some of his photos to illustrate our story.

Picture taken by Mr Square, with his Flatland-camera. (a) The sphere. (b) Selfie of Square (left) with the sphere (right).

As you can see on these photos, when you are stuck in Flatland and you take a picture of a sphere, only a segment is visible. What aroused Mr Square’s curiosity is the fact that the length of this segment changes constantly. Each picture shows a segment of a different length, due to the movement of the sphere along the z-axis, invisible to him. However, although they look random, Square discovered that these changing lengths can be explained without randomness by introducing a hidden variable living in a hypothetical third dimension. The apparent randomness is simply a consequence of his incomplete knowledge of the system: The position along the hidden variable axis z is inaccessible! Of course, this is only a model, this third dimension is purely theoretical, and no one from Flatland will ever visit it.

What about quantum mechanics?

Measurement outcomes are random as well in the quantum realm. Can we explain the randomness in quantum measurements by a hidden variable? Surprisingly, the answer is no! Von Neumann, one of the greatest scientists of the 20th century, was the first one to make this claim in 1932. His attempt to prove this result is known today as “Von Neumann’s silly mistake”. It was not until 1966 that Bell convinced the community that Von Neumann’s argument relies on a silly assumption.

Consider first a system of a single quantum bit, or qubit. A qubit is a 2-level system. It can be either in a ground state or in an excited state, but also in a quantum superposition |\psi\rangle = \alpha |g\rangle + \beta|e\rangle of these two states, where \alpha and \beta are complex numbers such that |\alpha|^2 + |\beta|^2 = 1. We can see this quantum state as a 2-dimensional vector (\alpha, \beta), where the ground state is |g\rangle=(1,0) and the excited state is |e\rangle=(0,1).


The probability of an outcome depends on the projection of the quantum state onto the ground state and the excited state.

What can we measure about this qubit? First, imagine that we want to know if our quantum state is in the ground state or in the excited state. There is a quantum measurement that returns a random outcome, which is g with probability P(g) = |\alpha|^2 and e with probability P(e) = |\beta|^2.

Let us try to reinterpret this measurement in a different way. Inspired by Mr Square’s idea, we extend our description of the state |\psi\rangle of the system to include the outcome as an extra parameter. In this model, a state is a pair of the form (|\psi\rangle, \lambda) where \lambda is either e or g. Our quantum state can be seen as being in position (|\psi\rangle, g) with probability P(g) or in position (|\psi\rangle, e) with probability P(e). Measuring only reveals the value of the hidden variable \lambda. By introducing a hidden variable, we made this measurement deterministic. This proves that the randomness can be moved to the level of the description of the state, just as in Flatland. The weirdness of quantum mechanics goes away.

Contextuality of quantum mechanics

Let us try to extend our hidden variable model to all quantum measurements. We can associate a measurement with a particular kind of matrix A, called an observable. Measuring an observable returns randomly one of its eigenvalue. For instance, the Pauli matrices

Z =  \begin{pmatrix}  1 & 0\\  0 & -1\\  \end{pmatrix}  \quad \text{ and } \quad  X =  \begin{pmatrix}  0 & 1\\  1 & 0\\  \end{pmatrix},

as well as Y = iZX and the identity matrix I, are 1-qubit observables with eigenvalues (i.e. measurement outcomes) \pm 1. Now, take a system of 2 qubits. Since each of the 2 qubits can be either excited or not, our quantum state is a 4-dimensional vector

|\psi\rangle = \alpha |g_1\rangle \otimes |g_2\rangle  + \beta |g_1\rangle \otimes |e_2\rangle  + \gamma |e_1\rangle \otimes |g_2\rangle  + \delta |e_1\rangle \otimes |e_2\rangle.

Therein, the 4 vectors |x\rangle \otimes |y\rangle can be identified with the vectors of the canonical basis (1000), (0100), (0010) and (0001). We will consider the measurement of 2-qubit observables of the form A \otimes B defined by A \otimes B |x\rangle \otimes |y\rangle = A |x\rangle \otimes B |y\rangle. In other words, A acts on the first qubit and B acts on the second one. Later, we will look into the observables X \otimes I, Z \otimes I, I \otimes X, I \otimes Z and their products.

What happens when two observables are measured simultaneously? In quantum mechanics, we can measure simultaneously multiple observables if these observables commute with each other. In that case, measuring O then O', or measuring O' first and then O, doesn’t make any difference. Therefore, we say that these observables are measured simultaneously, the outcome being a pair (\lambda,\lambda'), composed of an eigenvalue of O and an eigenvalue of O'. Their product O'' = OO', which commutes with both O and O', can also be measured in the same time. Measuring this triple returns a triple of eigenvalues (\lambda,\lambda',\lambda'') corresponding respectively to O, O' and O''. The relation O'' = OO' imposes the constraint

(1)               \qquad \lambda'' = \lambda \lambda'

on the outcomes.

Assume that one can describe the result of all quantum measurements with a model such that, for all observables O and for all states \nu of the model, a deterministic outcome \lambda_\nu(O) exists. Here, \nu is our ‘extended’, not necessarily physical, description of the state of the system. When O and O' are commuting, it is reasonable to assume that the relation (1) holds also at the level of the hidden variable model, namely

(2)                \lambda_\nu(OO') = \lambda_\nu(O) \cdot \lambda_\nu(O').

Such a model is called a non-contextual hidden variable model. Von Neumann proved that no such value \lambda_\nu exists by considering these relations for all pairs O, O' of observables. This shows that quantum mechanics is contextual! Hum… Wait a minute. It seems silly to impose such a constraint for all pairs of observable, including those that cannot be measured simultaneously. This is “Von Neumann’s silly assumption’. Only pairs of commuting observables should be considered.


Peres-Mermin proof of contextuality

One can resurrect Von Neumann’s argument, assuming Eq.(2) only for commuting observables. Peres-Mermin’s square provides an elegant proof of this result. Form a 3 \times 3 array with these observables. It is constructed in such a way that

(i) The eigenvalues of all the observables in Peres-Mermin’s square are ±1,

(ii) Each row and each column is a triple of commuting observables,

(iii) The last element of each row and each column is the product of the 2 first observables, except in the last column where Y \otimes Y = -(Z \otimes Z)(X \otimes X).

If a non-contextual hidden variable exists, it associates fixed eigenvalues a, b, c, d (which are either 1 or -1) with the 4 observables X \otimes I, Z \otimes I, I \otimes X, I \otimes Z. Applying Eq.(2) to the first 2 rows and to the first 2 columns, one deduces the values of all the observables of the square, except Y \otimes Y . Finally, what value should be attributed to Y \otimes Y? By (iii), applying Eq.(2) to the last row, one gets \lambda_\nu(Y \otimes Y) = abcd. However, using the last column, (iii) and Eq.(2) yield the opposite value \lambda_\nu (Y \otimes Y ) = -abcd. This is the expected contradiction, proving that there is no non-contextual value \lambda_\nu. Quantum mechanics is contextual!

We saw that the randomness in quantum measurements cannot be explained in a ‘classical’ way. Besides its fundamental importance, this result also influences quantum technologies. What I really care about is how to construct a quantum computer, or more generally, I would like to understand what kind of quantum device could be superior to its classical counterpart for certain tasks. Such a quantum advantage can only be reached by exploiting the weirdness of quantum mechanics, such as contextuality 1,2,3,4,5. Understanding these weird phenomena is one of the first tasks to accomplish.

Happy Halloween from…the discrete Wigner function?

Do you hope to feel a breath of cold air on the back of your neck this Halloween? I’ve felt one literally: I earned my Masters in the icebox called “Ontario,” at the Perimeter Institute for Theoretical Physics. Perimeter’s colloquia1 take place in an auditorium blacker than a Quentin Tarantino film. Aephraim Steinberg presented a colloquium one air-conditioned May.

Steinberg experiments on ultracold atoms and quantum optics2 at the University of Toronto. He introduced an idea that reminds me of biting into an apple whose coating you’d thought consisted of caramel, then tasting blood: a negative (quasi)probability.

Probabilities usually range from zero upward. Consider Shirley Jackson’s short story The Lottery. Villagers in a 20th-century American village prepare slips of paper. The number of slips equals the number of families in the village. One slip bears a black spot. Each family receives a slip. Each family has a probability p > 0  of receiving the marked slip. What happens to the family that receives the black spot? Read Jackson’s story—if you can stomach more than a Tarantino film.

Jackson peeled off skin to reveal the offal of human nature. Steinberg’s experiments reveal the offal of Nature. I’d expect humaneness of Jackson’s villagers and nonnegativity of probabilities. But what looks like a probability and smells like a probability might be hiding its odor with Special-Edition Autumn-Harvest Febreeze.


A quantum state resembles a set of classical3 probabilities. Consider a classical system that has too many components for us to track them all. Consider, for example, the cold breath on the back of your neck. The breath consists of air molecules at some temperature T. Suppose we measured the molecules’ positions and momenta. We’d have some probability p_1 of finding this particle here with this momentum, that particle there with that momentum, and so on. We’d have a probability p_2 of finding this particle there with that momentum, that particle here with this momentum, and so on. These probabilities form the air’s state.

We can tell a similar story about a quantum system. Consider the quantum light prepared in a Toronto lab. The light has properties analogous to position and momentum. We can represent the light’s state with a mathematical object similar to the air’s probability density.4 But this probability-like object can sink below zero. We call the object a quasiprobability, denoted by \mu.

If a \mu sinks below zero, the quantum state it represents encodes entanglement. Entanglement is a correlation stronger than any achievable with nonquantum systems. Quantum information scientists use entanglement to teleport information, encrypt messages, and probe the nature of space-time. I usually avoid this cliché, but since Halloween is approaching: Einstein called entanglement “spooky action at a distance.”


Eugene Wigner and others defined quasiprobabilities shortly before Shirley Jackson wrote The Lottery. Quantum opticians use these \mu’s, because quantum optics and quasiprobabilities involve continuous variables. Examples of continuous variables include position: An air molecule can sit at this point (e.g., x = 0) or at that point (e.g., x = 1) or anywhere between the two (e.g., x = 0.001). The possible positions form a continuous set. Continuous variables model quantum optics as they model air molecules’ positions.

Information scientists use continuous variables less than we use discrete variables. A discrete variable assumes one of just a few possible values, such as 0 or 1, or trick or treat.


How a quantum-information theorist views Halloween.

Quantum-information scientists study discrete systems, such as electron spins. Can we represent discrete quantum systems with quasiprobabilities \mu as we represent continuous quantum systems? You bet your barmbrack.

Bill Wootters and others have designed quasiprobabilities for discrete systems. Wootters stipulated that his \mu have certain properties. The properties appear in this review.  Most physicists label properties “1,” “2,” etc. or “Prop. 1,” “Prop. 2,” etc. The Wootters properties in this review have labels suited to Halloween.


Seeing (quasi)probabilities sink below zero feels like biting into an apple that you think has a caramel coating, then tasting blood. Did you eat caramel apples around age six? Caramel apples dislodge baby teeth. When baby teeth fall out, so does blood. Tasting blood can mark growth—as does the squeamishness induced by a colloquium that spooks a student. Who needs haunted mansions when you have negative quasiprobabilities?


For nonexperts:

1Weekly research presentations attended by a department.


3Nonquantum (basically).

4Think “set of probabilities.”

Tripping over my own inner product

A scrape stood out on the back of my left hand. The scrape had turned greenish-purple, I noticed while opening the lecture-hall door. I’d jounced the hand against my dining-room table while standing up after breakfast. The table’s corners form ninety-degree angles. The backs of hands do not.

Earlier, when presenting a seminar, I’d forgotten to reference papers by colleagues. Earlier, I’d offended an old friend without knowing how. Some people put their feet in their mouths. I felt liable to swallow a clog.

The lecture was for Ph 219: Quantum ComputationI was TAing (working as a teaching assistant for) the course. John Preskill was discussing quantum error correction.

Computers suffer from errors as humans do: Imagine setting a hard drive on a table. Coffee might spill on the table (as it probably would have if I’d been holding a mug near the table that week). If the table is in my California dining room, an earthquake might judder the table. Juddering bangs the hard drive against the wood, breaking molecular bonds and deforming the hardware. The information stored in computers degrades.

How can we protect information? By encoding it—by translating the message into a longer, encrypted message. An earthquake might judder the encoded message. We can reverse some of the damage by error-correcting.

Different types of math describe different codes. John introduced a type of math called symplectic vector spaces. “Symplectic vector space” sounds to me like a garden of spiny cacti (on which I’d probably have pricked fingers that week). Symplectic vector spaces help us translate between the original and encoded messages.


Symplectic vector space?

Say that an earthquake has juddered our hard drive. We want to assess how the earthquake corrupted the encoded message and to error-correct. Our encryption scheme dictates which operations we should perform. Each possible operation, we represent with a mathematical object called a vector. A vector can take the form of a list of numbers.

We construct the code’s vectors like so. Say that our quantum hard drive consists of seven phosphorus nuclei atop a strip of silicon. Each nucleus has two observables, or measurable properties. Let’s call the observables Z and X.

Suppose that we should measure the first nucleus’s Z. The first number in our symplectic vector is 1. If we shouldn’t measure the first nucleus’s Z, the first number is 0. If we should measure the second nucleus’s Z, the second number is 1; if not, 0; and so on for the other nuclei. We’ve assembled the first seven numbers in our vector. The final seven numbers dictate which nuclei’s Xs we measure. An example vector looks like this: ( 1, \, 0, \, 1, \, 0, \, 1, \, 0, \, 1 \; | \; 0, \, 0, \, 0, \, 0, \, 0, \, 0, \, 0 ).

The vector dictates that we measure four Zs and no Xs.


Symplectic vectors represent the operations we should perform to correct errors.

A vector space is a collection of vectors. Many problems—not only codes—involve vector spaces. Have you used Google Maps? Google illustrates the step that you should take next with an arrow. We can represent that arrow with a vector. A vector, recall, can take the form of a list of numbers. The step’s list of twonumbers indicates whether you should walk ( \text{Northward or not} \; | \; \text{Westward or not} ).


I’d forgotten about my scrape by this point in the lecture. John’s next point wiped even cacti from my mind.

Say you want to know how similar two vectors are. You usually calculate an inner product. A vector v tends to have a large inner product with any vector w that points parallel to v.


Parallel vectors tend to have a large inner product.

The vector v tends to have an inner product of zero with any vector w that points perpendicularly. Such v and w are said to annihilate each other. By the end of a three-hour marathon of a research conversation, we might say that v and w “destroy” each other. v is orthogonal to w.


Two orthogonal vectors, having an inner product of zero, annihilate each other.

You might expect a vector v to have a huge inner product with itself, since v points parallel to v. Quantum-code vectors defy expectations. In a symplectic vector space, John said, “you can be orthogonal to yourself.”

A symplectic vector2 can annihilate itself, destroy itself, stand in its own way. A vector can oppose itself, contradict itself, trip over its own feet. I felt like I was tripping over my feet that week. But I’m human. A vector is a mathematical ideal. If a mathematical ideal could be orthogonal to itself, I could allow myself space to err.


Tripping over my own inner product.

Lloyd Alexander wrote one of my favorite books, the children’s novel The Book of Three. The novel features a stout old farmer called Coll. Coll admonishes an apprentice who’s burned his fingers: “See much, study much, suffer much.” We smart while growing smarter.

An ant-sized scar remains on the back of my left hand. The scar has been fading, or so I like to believe. I embed references to colleagues’ work in seminar Powerpoints, so that I don’t forget to cite anyone. I apologized to the friend, and I know about symplectic vector spaces. We all deserve space to err, provided that we correct ourselves. Here’s to standing up more carefully after breakfast.


1Not that I advocate for limiting each coordinate to one bit in a Google Maps vector. The two-bit assumption simplifies the example.

2Not only symplectic vectors are orthogonal to themselves, John pointed out. Consider a string of bits that contains an even number of ones. Examples include (0, 0, 0, 0, 1, 1). Each such string has a bit-wise inner product, over the field {\mathbb Z}_2, of zero with itself.

Building the future

At the start of the academic year, my high school Physics students want an easy lab with simple, clear-cut data.  They are satisfied with a clear-cut conclusion. Open-ended labs, especially those without cookbook procedures are at first daunting and intimidating.  Having to take time to troubleshoot a problem is a painful process for them, as it can be for many.  As the year progresses, they seem to grow more comfortable with their own exploration of Physics trends.


Another happy day in Sloan

There is no set manual for real scientific research, for uncharted territory. Exciting, new research has no “right” answer upon which to compare your data. And building your own, unique experimental set-up inherently requires much time to minimize new issues. It is interesting to me that when there is less guidance based on previous research, there is a larger possibility for great, new discoveries.

This summer I again retreated from the summer heat, plunging into the Caltech sub basements to further my understanding of the freshest research, efficient laboratory techniques, and culture in Physics research. The quiet hum of the air conditioner and lights marked an eerie contrast to the non-stop, bustling life of the classroom. It was an even more stark contrast to my 16-month-old daughter’s incessant joyful and curious exploration of the world.


The SEM Chamber

My first project this summer focused on helping to get the SEM (Scanning Electron Microscope) up and running. Once the SEM is functional the first samples it will scan are solar cells comprised of graphene nanotubes. If grand scaled and mass produced, methane may be one source of the necessary carbon for graphene. What if we contained methane gases that are already problematically being released into our greenhouse-gas-ridden atmosphere and subsequently used them to make graphene solar cells? What a win-win solution to help the daunting problem of global climate change?

Helping to set up the SEM involved a variety of interesting tasks: I found the working distance from the SEM gun to the sample holder that would soon be loaded into the chamber. I researched Pirani gauge parts and later rubber pads to help with damping. I helped to install copper ConFlat flanges for making low pressure seals. We used sonification to clean parts used at the SEM lab. We found and installed a nitrogen (N2) line to flush out moisture in the SEM chamber. There were numerous rounds of baking out moisture that may have collected in the chamber in the years since this SEM was last in use.


A tube scanner head

During “down time”, such as when the SEM chamber was being pumped down to less than one-part-per-billion pressure with multiple vacuum pumps, we directed our attention to two other projects. The first was making parts for the tube scanner head. Due to the possibility of burning out scanner heads in the alignment process when we first turn on the SEM gun, we needed to be prepared with alternative STM parts. This involved drilling, epoxying, baking, sanding, and soldering tiny pieces.  A diminutive coaxial cable with multiple insulating layers was stripped apart so that we could properly connect the gold conducting wire from within.

During the last week I focused my efforts by returning to an interferometer set up in the sub-basement of Sloan. Last summer, part of my time was spent learning about and setting up an interferometer system in order to measure the shift of a piezoelectric stack when particular voltages were applied. Once calibrated, these piezos will be used to control the motion of the tips in our lab’s STM (Scanning Tunneling Microscope). This summer was different because we had additional equipment from Thorlabs in order to move further along with the project.

Piezo Interferometer Pic 2

Overhead view of the interferometer set-up.

On the day of arrival of the much-needed parts, I felt like a child at Christmas. Ready, set, go. Racing against the impending end of the internship and start of the upcoming academic year, I worked to assemble our equipment.  


LASER, function generator, amplifier.

This same procedure was completed roughly a decade ago by graduate students in our lab. Now, though, the remaining calibrated piezos have been used. In order to continue doing important STM measurements, new piezo stacks need to be calibrated.

A ray of red, coherent light from our LASER is directed to a beamsplitter. One arm of light is directed to a mirror and reflected back to the beamsplitter. Another arm of light is directed to a mirror fixed upon the piezoelectric stack. Depending on the applied voltage and particular piezo stacks, the orientation and magnitude of the shear varies. A signal generator and amplifier are connected to the opposite end of the piezoelectric stacks to carefully control the voltage signal applied to the piezos.  Once the beams are recombined at the beamsplitter, they should interfere.  An interference pattern should be detected on the oscilloscope.


Confirmation that my oscilloscope was working properly

At first it was plain fun setting up the various parts, like fitting puzzle pieces with the various optics devices. The difficulty came later in troubleshooting. I had little issue with adjusting the set-up so that both beams from the LASER landed directly onto the photodetector. Getting a beautiful interference pattern was another case. Making sense of the output signal from the photodetector on the oscilloscope was also a process. Finding joy and benefit in the learning process as opposed to frustration in a trying time is an important lesson in life.  Of course it is inevitable that there will be difficulties in life. Can we grow from the learning opportunity as opposed to complaining about the struggle?


What I at first thought was the interference pattern I had been hoping for… Not so fast.

The irony is that just like my students, I wanted an easy, beautiful interference pattern that could be interpreted on our oscilloscope. I had the opportunity to learn through trial and error and from additional research on interferometers. I look forward to hearing from the lab group about the progress that is made on this project during the academic year while I am in the classroom. I am grateful to IQIM and the Yeh Lab Group for allowing me to continue participating in this exciting program.

Upending my equilibrium

Few settings foster equanimity like Canada’s Banff International Research Station (BIRS). Mountains tower above the center, softened by pines. Mornings have a crispness that would turn air fresheners evergreen with envy. The sky looks designed for a laundry-detergent label.


Doesn’t it?

One day into my visit, equilibrium shattered my equanimity.

I was participating in the conference “Beyond i.i.d. in information theory.” What “beyond i.i.d.” means is explained in these articles.  I was to present about resource theories for thermodynamics. Resource theories are simple models developed in quantum information theory. The original thermodynamic resource theory modeled systems that exchange energy and information.

Imagine a quantum computer built from tiny, cold, quantum circuits. An air particle might bounce off the circuit. The bounce can slow the particle down, transferring energy from particle to circuit. The bounce can entangle the particle with the circuit, transferring quantum information from computer to particle.

Suppose that particles bounced off the computer for ages. The computer would thermalize, or reach equilibrium: The computer’s energy would flatline. The computer would reach a state called the canonical ensemble. The canonical ensemble looks like this:  e^{ - \beta H }  / { Z }.

Joe Renes and I had extended these resource theories. Thermodynamic systems can exchange quantities other than energy and information. Imagine white-bean soup cooling on a stovetop. Gas condenses on the pot’s walls, and liquid evaporates. The soup exchanges not only heat, but also particles, with its environment. Imagine letting the soup cool for ages. It would thermalize to the grand canonical ensemble, e^{ - \beta (H - \mu N) } / { Z }. Joe and I had modeled systems that exchange diverse thermodynamic observables.*

What if, fellow beyond-i.i.d.-er Jonathan Oppenheim asked, those observables didn’t commute with each other?

Mathematical objects called operators represent observables. Let \hat{H} represent a system’s energy, and let \hat{N} represent the number of particles in the system. The operators fail to commute if multiplying them in one order differs from multiplying them in the opposite order: \hat{H}  \hat{N}  \neq  \hat{N}  \hat{H}.

Suppose that our quantum circuit has observables represented by noncommuting operators \hat{H} and \hat{N}. The circuit cannot have a well-defined energy and a well-defined particle number simultaneously. Physicists call this inability the Uncertainty Principle. Uncertainty and noncommutation infuse quantum mechanics as a Cashmere GlowTM infuses a Downy fabric softener.

Downy Cashmere Glow 2

Quantum uncertainty and noncommutation.

I glowed at Jonathan: All the coolness in Canada couldn’t have pleased me more than finding someone interested in that question.** Suppose that a quantum system exchanges observables \hat{Q}_1 and \hat{Q}_2 with the environment. Suppose that \hat{Q}_1 and \hat{Q}_2 don’t commute, like components \hat{S}_x and \hat{S}_y of quantum angular momentum. Would the system thermalize? Would the thermal state have the form e^{ \mu_1 \hat{Q}_1 + \mu_2 \hat{Q}_2 } / { Z }? Could we model the system with a resource theory?

Jonathan proposed that we chat.

The chat sucked in beyond-i.i.d.-ers Philippe Faist and Andreas Winter. We debated strategies while walking to dinner. We exchanged results on the conference building’s veranda. We huddled over a breakfast table after colleagues had pushed their chairs back. Information flowed from chalkboard to notebook; energy flowed in the form of coffee; food particles flowed onto the floor as we brushed crumbs from our notebooks.

Coffee, crumbs

Exchanges of energy and particles.

The idea morphed and split. It crystallized months later. We characterized, in three ways, the thermal state of a quantum system that exchanges noncommuting observables with its environment.

First, we generalized the microcanonical ensemble. The microcanonical ensemble is the thermal state of an isolated system. An isolated system exchanges no observables with any other system. The quantum computer and the air molecules can form an isolated system. So can the white-bean soup and its kitchen. Our quantum system and its environment form an isolated system. But they cannot necessarily occupy a microcanonical ensemble, thanks to noncommutation.

We generalized the microcanonical ensemble. The generalization involves approximation, unlikely measurement outcomes, and error tolerances. The microcanonical ensemble has a simple definition—sharp and clean as Banff air. We relaxed the definition to accommodate noncommutation. If the microcanonical ensemble resembles laundry detergent, our generalization resembles fabric softener.

Detergent vs. softener

Suppose that our system and its environment occupy this approximate microcanonical ensemble. Tracing out (mathematically ignoring) the environment yields the system’s thermal state. The thermal state basically has the form we expected, \gamma = e^{ \sum_j  \mu_j \hat{Q}_j } / { Z }.

This exponential state, we argued, follows also from time evolution. The white-bean soup equilibrates upon exchanging heat and particles with the kitchen air for ages. Our quantum system can exchange observables \hat{Q}_j with its environment for ages. The system equilibrates, we argued, to the state \gamma. The argument relies on a quantum-information tool called canonical typicality.

Third, we defined a resource theory for thermodynamic exchanges of noncommuting observables. In a thermodynamic resource theory, the thermal states are the worthless states: From a thermal state, one can’t extract energy usable to lift a weight or to power a laptop. The worthless states, we showed, have the form of \gamma.

Three path lead to the form \gamma of the thermal state of a quantum system that exchanges noncommuting observables with its environment. We published the results this summer.

Not only was Team Banff spilling coffee over \gamma. So were teams at Imperial College London and the University of Bristol. Our conclusions overlap, suggesting that everyone calculated correctly. Our methodologies differ, generating openings for exploration. The mountain passes between our peaks call out for mapping.

So does the path to physical reality. Do these thermal states form in labs? Could they? Cold atoms offer promise for realizations. In addition to experiments and simulations, master equations merit study. Dynamical typicality, Team Banff argued, suggests that \gamma results from equilibration. Master equations model equilibration. Does some Davies-type master equation have \gamma as its fixed point? Email me if you have leads!


Experimentalists, can you realize the thermal state e^{ \sum_j \mu_j \hat{Q}_j } / Z whose charges \hat{Q}_j don’t commute?


A photo of Banff could illustrate Merriam-Webster’s entry for “equanimity.” Banff equanimity deepened our understanding of quantum equilibrium. But we wouldn’t have understood quantum equilibrium if questions hadn’t shattered our tranquility. Give me the disequilibrium of recognizing problems, I pray, and the equilibrium to solve them.


*By “observable,” I mean “property that you can measure.”

**Teams at Imperial College London and Bristol asked that question, too. More pleasing than three times the coolness in Canada!