“Feveral kinds of hairy mouldy fpots”

Posted on June 12, 2014 by Nicole Yunger Halpern

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.

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).

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.”

^*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 theory of everything: Help wanted

Posted on June 2, 2014 by spiros

When Scientific American writes that physicists are working on a theory of everything, does it sound ambitious enough to you? Do you lie awake at night thinking that a theory of everything should be able to explain, well, everything? What if that theory is founded on quantum mechanics and finds a way to explain gravitation through the microscopic laws of the quantum realm? Would that be a grand unified theory of everything?

The answer is no, for two different, but equally important reasons. First, there is the inherent assumption that quantum systems change in time according to Schrodinger’s evolution: $i \hbar \partial_t \psi(t) = H \psi(t)$ . Why? Where does that equation come from? Is it a fundamental law of nature, or is it an emergent relationship between different states of the universe? What if the parameter $t$ , which we call time, as well as the linear, self-adjoint operator $H$ , which we call the Hamiltonian, are both emergent from a more fundamental, and highly typical phenomenon: the large amount of entanglement that is generically found when one decomposes the state space of a single, static quantum wavefunction, into two (different in size) subsystems: a clock and a space of configurations (on which our degrees of freedom live)? So many questions, so few answers.

The static multiverse

The perceptive reader may have noticed that I italicized the word ‘static’ above, when referring to the quantum wavefunction of the multiverse. The emphasis on static is on purpose. I want to make clear from the beginning that a theory of everything can only be based on axioms that are truly fundamental, in the sense that they cannot be derived from more general principles as special cases. How would you know that your fundamental principles are irreducible? You start with set theory and go from there. If that assumes too much already, then you work on your set theory axioms. On the other hand, if you can exhibit a more general principle from which your original concept derives, then you are on the right path towards more fundamentalness.

In that sense, time and space as we understand them, are not fundamental concepts. We can imagine an object that can only be in one state, like a switch that is stuck at the OFF position, never changing or evolving in any way, and we can certainly consider a complete graph of interactions between subsystems (the equivalent of a black hole in what we think of as space) with no local geometry in our space of configurations. So what would be more fundamental than time and space? Let’s start with time: The notion of an unordered set of numbers, such as $\{4,2,5,1,3,6,8,7,12,9,11,10\}$ , is a generalization of a clock, since we are only keeping the labels, but not their ordering. If we can show that a particular ordering emerges from a more fundamental assumption about the very existence of a theory of everything, then we have an understanding of time as a set of ordered labels, where each label corresponds to a particular configuration in the mathematical space containing our degrees of freedom. In that sense, the existence of the labels in the first place corresponds to a fundamental notion of potential for change, which is a prerequisite for the concept of time, which itself corresponds to constrained (ordered in some way) change from one label to the next. Our task is first to figure out where the labels of the clock come from, then where the illusion of evolution comes from in a static universe (Heisenberg evolution), and finally, where the arrow of time comes from in a macroscopic world (the illusion of irreversible evolution).

The axioms we ultimately choose must satisfy the following conditions simultaneously: 1. the implications stemming from these assumptions are not contradicted by observations, 2. replacing any one of these assumptions by its negation would lead to observable contradictions, and 3. the assumptions contain enough power to specify non-trivial structures in our theory. In short, as Immanuel Kant put it in his accessible bedtime story The critique of Pure Reason, we are looking for synthetic a priori knowledge that can explain space and time, which ironically were Kant’s answer to that same question.

The fundamental ingredients of the ultimate theory

Before someone decides to delve into the math behind the emergence of unitarity (Heisenberg evolution) and the nature of time, there is another reason why the grand unified theory of everything has to do more than just give a complete theory of how the most elementary subsystems in our universe interact and evolve. What is missing is the fact that quantity has a quality all its own. In other words, patterns emerge from seemingly complex data when we zoom out enough. This “zooming out” procedure manifests itself in two ways in physics: as coarse-graining of the data and as truncation and renormalization. These simple ideas allow us to reduce the computational complexity of evaluating the next state of a complex system: If most of the complexity of the system is hidden at a level you cannot even observe (think pre retina-display era), then all you have to keep track of is information at the macroscopic, coarse-grained level. On top of that, you can use truncation and renormalization to zero in on the most likely/ highest weight configurations your coarse-grained data can be in – you can safely throw away a billion configurations, if their combined weight is less than 0.1% of the total, because your super-compressed data will still give you the right answer with a fidelity of 99.9%. This is how you get to reduce a 9 GB raw video file down to a 300 MB Youtube video that streams over your WiFi connection without losing too much of the video quality.

I will not focus on the second requirement for the “theory of everything”, the dynamics of apparent complexity. I think that this fundamental task is the purview of other sciences, such as chemistry, biology, anthropology and sociology, which look at the “laws” of physics from higher and higher vantage points (increasingly coarse-graining the topology of the space of possible configurations). Here, I would like to argue that the foundation on which a theory of everything rests, at the basement level if such a thing exists, consists of four ingredients: Math, Hilbert spaces with tensor decompositions into subsystems, stability and compressibility. Now, you know about math (though maybe not of Zermelo-Fraenkel set theory), you may have heard of Hilbert spaces if you majored in math and/or physics, but you don’t know what stability, or compressibility mean in this context. So let me motivate the last two with a question and then explain in more detail below: What are the most fundamental assumptions that we sweep under the rug whenever we set out to create a theory of anything that can fit in a book – or ten thousand books – and still have predictive power? Stability and compressibility.

Math and Hilbert spaces are fundamental in the following sense: A theory needs a Language in order to encode the data one can extract from that theory through synthesis and analysis. The data will be statistical in the most general case (with every configuration/state we attach a probability/weight of that state conditional on an ambient configuration space, which will often be a subset of the total configuration space), since any observer creating a theory of the universe around them only has access to a subset of the total degrees of freedom. The remaining degrees of freedom, what quantum physicists group as the Environment, affect our own observations through entanglement with our own degrees of freedom. To capture this richness of correlations between seemingly uncorrelated degrees of freedom, the mathematical space encoding our data requires more than just a metric (i.e. an ability to measure distances between objects in that space) – it requires an inner-product: a way to measure angles between different objects, or equivalently, the ability to measure the amount of overlap between an input configuration and an output configuration, thus quantifying the notion of incremental change. Such mathematical spaces are precisely the Hilbert spaces mentioned above and contain states (with wavefunctions being a special case of such states) and operators acting on the states (with measurements, rotations and general observables being special cases of such operators). But, let’s get back to stability and compressibility, since these two concepts are not standard in physics.

Stability

Stability is that quality that says that if the theory makes a prediction about something observable, then we can test our theory by making observations on the state of the world and, more importantly, new observations do not contradict our theory. How can a theory fall apart if it is unstable? One simple way is to make predictions that are untestable, since they are metaphysical in nature (think of religious tenets). Another way is to make predictions that work for one level of coarse-grained observations and fail for a lower level of finer coarse-graining (think of Newtonian Mechanics). A more extreme case involves quantum mechanics assumed to be the true underlying theory of physics, which could still fail to produce a stable theory of how the world works from our point of view. For example, say that your measurement apparatus here on earth is strongly entangled with the current state of a star that happens to go supernova 100 light-years from Earth during the time of your experiment. If there is no bound on the propagation speed of the information between these two subsystems, then your apparatus is engulfed in flames for no apparent reason and you get random data, where you expected to get the same “reproducible” statistics as last week. With no bound on the speed with which information can travel between subsystems of the universe, our ability to explain and/or predict certain observations goes out the window, since our data on these subsystems will look like white noise, an illusion of randomness stemming from the influence of inaccessible degrees of freedom acting on our measurement device. But stability has another dimension; that of continuity. We take for granted our ability to extrapolate the curve that fits 1000 data points on a plot. If we don’t assume continuity (and maybe even a certain level of smoothness) of the data, then all bets are off until we make more measurements and gather additional data points. But even then, we can never gather an infinite (let alone, uncountable) number of data points – we must extrapolate from what we have and assume that the full distribution of the data is close in norm to our current dataset (a norm is a measure of distance between states in the Hilbert space).

The emergence of the speed of light

The assumption of stability may seem trivial, but it holds within it an anthropic-style explanation for the bound on the speed of light. If there is no finite speed of propagation for the information between subsystems that are “far apart”, from our point of view, then we will most likely see randomness where there is order. A theory needs order. So, what does it mean to be “far apart” if we have made no assumption for the existence of an underlying geometry, or spacetime for that matter? There is a very important concept in mathematical physics that generalizes the concept of the speed of light for non-relativistic quantum systems whose subsystems live on a graph (i.e. where there may be no spatial locality or apparent geometry): the Lieb-Robinson velocity. Those of us working at the intersection of mathematical physics and quantum many-body physics, have seen first-hand the powerful results one can get from the existence of such an effective and emergent finite speed of propagation of information between quantum subsystems that, in principle, can signal to each other instantaneously through the action of a non-local unitary operator (rotation of the full system under Heisenberg evolution). It turns out that under certain natural assumptions on the graph of interactions between the different subsystems of a many-body quantum system, such a finite speed of light emerges naturally. The main requirement on the graph comes from the following intuitive picture: If each node in your graph is connected to only a few other nodes and the number of paths between any two nodes is bounded above in some nice way (say, polynomially in the distance between the nodes), then communication between two distant nodes will take time proportional to the distance between the nodes (in graph distance units, the smallest number of nodes among all paths connecting the two nodes). Why? Because at each time step you can only communicate with your neighbors and in the next time step they will communicate with theirs and so on, until one (and then another, and another) of these communication cascades reaches the other node. Since you have a bound on how many of these cascades will eventually reach the target node, the intensity of the communication wave is bounded by the effective action of a single messenger traveling along a typical path with a bounded speed towards the destination. There should be generalizations to weighted graphs, but this area of mathematical physics is still really active and new results on bounds on the Lieb-Robinson velocity gather attention very quickly.

Escaping black holes

If this idea holds any water, then black holes are indeed nearly complete graphs, where the notion of space and time breaks down, since there is no effective bound on the speed with which information propagates from one node to another. The only way to escape is to find yourself at the boundary of the complete graph, where the nodes of the black hole’s apparent horizon are connected to low-degree nodes outside. Once you get to a low-degree node, you need to keep moving towards other low-degree nodes in order to escape the “gravitational pull” of the black hole’s super-connectivity. In other words, gravitation in this picture is an entropic force: we gravitate towards massive objects for the same reason that we “gravitate” towards the direction of the arrow of time: we tend towards higher entropy configurations – the probability of reaching the neighborhood of a set of highly connected nodes is much, much higher than hanging out for long near a set of low-degree nodes in the same connected component of the graph. If a graph has disconnected components, then their is no way to communicate between the corresponding spacetimes – their states are in a tensor product with each other. One has to carefully define entanglement between components of a graph, before giving a unified picture of how spatial geometry arises from entanglement. Somebody get to it.

Erik Verlinde has introduced the idea of gravity as an entropic force and Fotini Markopoulou, et al. have introduced the notion of quantum graphity (gravity emerging from graph models). I think these approaches must be taken seriously, if only because they work with more fundamental principles than the ones found in Quantum Field Theory and General Relativity. After all, this type of blue sky thinking has led to other beautiful connections, such as ER=EPR (the idea that whenever two systems are entangled, they are connected by a wormhole). Even if we were to disagree with these ideas for some technical reason, we must admit that they are at least trying to figure out the fundamental principles that guide the things we take for granted. Of course, one may disagree with certain attempts at identifying unifying principles simply because the attempts lack the technical gravitas that allows for testing and calculations. Which is why a technical blog post on the emergence of time from entanglement is in the works.

Compressibility

So, what about that last assumption we seem to take for granted? How can you have a theory you can fit in a book about a sequence of events, or snapshots of the state of the observable universe, if these snapshots look like the static noise on a TV screen with no transmission signal? Well, you can’t! The fundamental concept here is Kolmogorov complexity and its connection to randomness/predictability. A sequence of data bits like:

10011010101101001110100001011010011101010111010100011010110111011110

has higher complexity (and hence looks more random/less predictable) than the sequence:

10101010101010101010101010101010101010101010101010101010101010101010

because there is a small computer program that can output each successive bit of the latter sequence (even if it had a million bits), but (most likely) not of the former. In particular, to get the second sequence with one million bits one can write the following short program:

string s = ’10’;
for n=1 to $499,999$ :
s.append(’10’);
n++;
end
print s;

As the number of bits grows, one may wonder if the number of iterations (given above by $499,999$ ), can be further compressed to make the program even smaller. The answer is yes: The number $499,999$ in binary requires $\log_2 499,999$ bits, but that binary number is a string of 0s and 1s, so it has its own Kolmogorov complexity, which may be smaller than $\log_2 499,999$ . So, compressibility has a strong element of recursion, something that in physics we associate with scale invariance and fractals.

You may be wondering whether there are truly complex sequences of 0,1 bits, or if one can always find a really clever computer program to compress any N bit string down to, say, N/100 bits. The answer is interesting: There is no computer program that can compute the Kolmogorov complexity of an arbitrary string (the argument has roots in Berry’s Paradox), but there are strings of arbitrarily large Kolmogorov complexity (that is, no matter what program we use and what language we write it in, the smallest program (in bits) that outputs the N-bit string will be at least N bits long). In other words, there really are streams of data (in the form of bits) that are completely incompressible. In fact, a typical string of 0s and 1s will be almost completely incompressible!

Stability, compressibility and the arrow of time

So, what does compressibility have to do with the theory of everything? It has everything to do with it. Because, if we ever succeed in writing down such a theory in a physics textbook, we will have effectively produced a computer program that, given enough time, should be able to compute the next bit in the string that represents the data encoding the coarse-grained information we hope to extract from the state of the universe. In other words, the only reason the universe makes sense to us is because the data we gather about its state is highly compressible. This seems to imply that this universe is really, really special and completely atypical. Or is it the other way around? What if the laws of physics were non-existent? Would there be any consistent gravitational pull between matter to form galaxies and stars and planets? Would there be any predictability in the motion of the planets around suns? Forget about life, let alone intelligent life and the anthropic principle. Would the Earth, or Jupiter even know where to go next if it had no sense that it was part of a non-random plot in the movie that is spacetime? Would there be any notion of spacetime to begin with? Or an arrow of time? When you are given one thousand frames from one thousand different movies, there is no way to make a single coherent plot. Even the frames of a single movie would make little sense upon reshuffling.

What if the arrow of time emerged from the notions of stability and compressibility, through coarse-graining that acts as a compression algorithm for data that is inherently highly-complex and, hence, highly typical as the next move to make? If two strings of data look equally complex upon coarse-graining, but one of them has a billion more ways of appearing from the underlying raw data, then which one will be more likely to appear in the theory-of-everything book of our coarse-grained universe? Note that we need both high compressibility after coarse-graining in order to write down the theory, as well as large entropy before coarse-graining (from a large number of raw strings that all map to one string after coarse-graining), in order to have an arrow of time. It seems that we need highly-typical, highly complex strings that become easy to write down once we coarse grain the data in some clever way. Doesn’t that seem like a contradiction? How can a bunch of incompressible data become easily compressible upon coarse-graining? Here is one way: Take an N-bit string and define its 1-bit coarse-graining as the boolean AND of its digits. All but one strings will default to 0. The all 1s string will default to 1. Equally compressible, but the probability of seeing the 1 after coarse-graining is $2^{-N}$ . With only 300 bits, finding the coarse-grained 1 is harder than looking for a specific atom in the observable universe. In other words, if the coarse-graining rule at time t is the one given above, then you can be pretty sure you will be seeing a 0 come up next in your data. Notice that before coarse-graining, all $2^N$ strings are equally likely, so there is no arrow of time, since there is no preferred string from a probabilistic point of view.

Conclusion, for now

When we think about the world around us, we go to our intuitions first as a starting point for any theory describing the multitude of possible experiences (observable states of the world). If we are to really get to the bottom of this process, it seems fruitful to ask “why do I assume this?” and “is that truly fundamental or can I derive it from something else that I already assumed was an independent axiom?” One of the postulates of quantum mechanics is the axiom corresponding to the evolution of states under Schrodinger’s equation. We will attempt to derive that equation from the other postulates in an upcoming post. Until then, your help is wanted with the march towards more fundamental principles that explain our seemingly self-evident truths. Question everything, especially when you think you really figured things out. Start with this post. After all, a theory of everything should be able to explain itself.

UP NEXT: Entanglement, Schmidt decomposition, concentration measure bounds and the emergence of discrete time and unitary evolution.

John Preskill and the dawn of the entanglement frontier

Posted on May 22, 2014 by spiros

Editor’s Note: John Preskill’s recent election to the National Academy of Sciences generated a lot of enthusiasm among his colleagues and students. In an earlier post today, famed Stanford theoretical physicist, Leonard Susskind, paid tribute to John’s early contributions to physics ranging from magnetic monopoles to the quantum mechanics of black holes. In this post, Daniel Gottesman, a faculty member at the Perimeter Institute, takes us back to the formative years of the Institute for Quantum Information at Caltech, the precursor to IQIM and a world-renowned incubator for quantum information and quantum computation research. Though John shies away from the spotlight, we, at IQIM, believe that the integrity of his character and his role as a mentor and catalyst for science are worthy of attention and set a good example for current and future generations of theoretical physicists.

Preskill’s legacy may well be the incredible number of preeminent research scientists in quantum physics he has mentored throughout his extraordinary career.

When someone wins a big award, it has become traditional on this blog for John Preskill to write something about them. The system breaks down, though, when John is the one winning the award. Therefore I’ve been brought in as a pinch hitter (or should it be pinch lionizer?).

The award in this case is that John has been elected to the National Academy of Sciences, along with Charlie Kane and a number of other people that don’t work on quantum information. Lenny Susskind has already written about John’s work on other topics; I will focus on quantum information.

On the research side of quantum information, John is probably best known for his work on fault-tolerant quantum computation, particularly topological fault tolerance. John jumped into the field of quantum computation in 1994 in the wake of Shor’s algorithm, and brought me and some of his other grad students with him. It was obvious from the start that error correction was an important theoretical challenge (emphasized, for instance, by Unruh), so that was one of the things we looked at. We couldn’t figure out how to do it, but some other people did. John and I embarked on a long drawn-out project to get good bounds on the threshold error rate. If you can build a quantum computer with an error rate below the threshold value, you can do arbitrarily large quantum computations. If not, then errors will eventually overwhelm you. Early versions of my project with John suggested that the threshold should be about $10^{-4}$ , and the number began floating around (somewhat embarrassingly) as the definitive word on the threshold value. Our attempts to bound the higher-order terms in the computation became rather grotesque, and the project proceeded very slowly until a new approach and the recruitment of Panos Aliferis finally let us finish a paper with a rigorous proof of a slightly lower threshold value.

Meanwhile, John had also been working on topological quantum computation. John has already written about his excitement when Kitaev visited Caltech and talked about the toric code. The two of them, plus Eric Dennis and Andrew Landahl, studied the application of this code for fault tolerance. If you look at the citations of this paper over time, it looks rather … exponential. For a while, topological things were too exotic for most quantum computer people, but over time, the virtues of surface codes have become obvious (apparently high threshold, convenient for two-dimensional architectures). It’s become one of the hot topics in recent years and there are no signs of flagging interest in the community.

John has also made some important contributions to security proofs for quantum key distribution, known to the cognoscenti just by its initials. QKD allows two people (almost invariably named Alice and Bob) to establish a secret key by sending qubits over an insecure channel. If the eavesdropper Eve tries to live up to her name, her measurements of the qubits being transmitted will cause errors revealing her presence. If Alice and Bob don’t detect the presence of Eve, they conclude that she is not listening in (or at any rate hasn’t learned much about the secret key) and therefore they can be confident of security when they later use the secret key to encrypt a secret message. With Peter Shor, John gave a security proof of the best-known QKD protocol, known as the “Shor-Preskill” proof. Sometimes we scientists lack originality in naming. It was not the first proof of security, but earlier ones were rather complicated. The Shor-Preskill proof was conceptually much clearer and made a beautiful connection between the properties of quantum error-correcting codes and QKD. The techniques introduced in their paper got adopted into much later work on quantum cryptography.

Collaborating with John is always an interesting experience. Sometimes we’ll discuss some idea or some topic and it will be clear that John does not understand the idea clearly or knows little about the topic. Then, a few days later we discuss the same subject again and John is an expert, or at least he knows a lot more than me. I guess this ability to master
topics quickly is why he was always able to answer Steve Flammia’s random questions after lunch. And then when it comes time to write the paper … John will do it. It’s not just that he will volunteer to write the first draft — he keeps control of the whole paper and generally won’t let you edit the source, although of course he will incorporate your comments. I think this habit started because of incompatibilities between the TeX editor he was using and any other program, but he maintains it (I believe) to make sure that the paper meets his high standards of presentation quality.

This also explains why John has been so successful as an expositor. His
lecture notes for the quantum computation class at Caltech are well-known. Despite being incomplete and not available on Amazon, they are probably almost as widely read as the standard textbook by Nielsen and Chuang.

Before IQIM, there was IQI, and before that was QUIC.

He apparently is also good at writing grants. Under his leadership and Jeff Kimble’s, Caltech has become one of the top places for quantum computation. In my last year of graduate school, John and Jeff, along with Steve Koonin, secured the QUIC grant, and all of a sudden Caltech had money for quantum computation. I got a research assistantship and could write my thesis without having to worry about TAing. Postdocs started to come — first Chris Fuchs, then a long stream of illustrious others. The QUIC grant grew into IQI, and that eventually sprouted an M and drew in even more people. When I was a student, John’s group was located in Lauritsen with the particle theory group. We had maybe three grad student offices (and not all the students were working on quantum information), plus John’s office. As the Caltech quantum effort grew, IQI acquired territory in another building, then another, and then moved into a good chunk of the new Annenberg building. Without John’s efforts, the quantum computing program at Caltech would certainly be much smaller and maybe completely lacking a theory side. It’s also unlikely this blog would exist.

The National Academy has now elected John a member, probably more for his research than his twitter account (@preskill), though I suppose you never know. Anyway, congratulations, John!

-D. Gottesman

Of magnetic monopoles and fast-scrambling black holes

Posted on May 22, 2014 by spiros

Editor’s Note: On April 29th, 2014, the National Academy of Sciences announced the new electees to the prestigious organization. This was an especially happy occasion for everyone here at IQIM, since the new members included our very own John Preskill, Richard P. Feynman Professor of Theoretical Physics and regular blogger on this site. A request was sent to Leonard Susskind, a close friend and collaborator of John’s, to take a trip down memory lane and give the rest of us a glimpse of some of John’s early contributions to Physics. John, congratulations from all of us here at IQIM.

John Preskill was elected to the National Academy of Sciences, an event long overdue. Perhaps it took longer than it should have because there is no way to pigeon-hole him; he is a theoretical physicist, and that’s all there is to it.

John has long been one of my heroes in theoretical physics. There is something very special about his work. It has exceptional clarity, it has vision, it has integrity—you can count on it. And sometimes it has another property: it can surprise. The first time I heard his name come up, sometime around 1979, I was not only surprised; I was dismayed. A student whose name I had never heard of, had uncovered a serious clash between two things, both of which I deeply wanted to believe in. One was the Big-Bang theory and the other was the discovery of grand unified particle theories. Unification led to the extraordinary prediction that Dirac’s magnetic monopoles must exist, at least in principle. The Big-Bang theory said they must exist in fact. The extreme conditions at the beginning of the universe were exactly what was needed to create loads of monopoles; so many that they would flood the universe with too much mass. John, the unknown graduate student, did a masterful analysis. It left no doubt that something had to give. Cosmology gave. About a year later, inflationary cosmology was discovered by Guth who was in part motivated by Preskill’s monopole puzzle.

John’s subsequent career as a particle physicist was marked by a number of important insights which often had that surprising quality. The cosmology of the invisible axion was one. Others had to do with very subtle and counterintuitive features of quantum field theory, like the existence of “Alice strings”. In the very distant past, Roger Penrose and I had a peculiar conversation about possible generalizations of the Aharonov-Bohm effect. We speculated on all sorts of things that might happen when something is transported around a string. I think it was Roger who got excited about the possibilities that might result if a topological defect could change gender. Alice strings were not quite that exotic, only electric charge flips, but nevertheless it was very surprising.

John of course had a long standing interest in the quantum mechanics of black holes: I will quote a passage from a visionary 1992 review paper, “Do Black Holes Destroy Information?”

“I conclude that the information loss paradox may well presage a revolution in fundamental physics.”

At that time no one knew the answer to the paradox, although a few of us, including John, thought the answer was that information could not be lost. But almost no one saw the future as clearly as John did. Our paths crossed in 1993 in a very exciting discussion about black holes and information. We were both thinking about the same thing, now called black hole complementarity. We were concerned about quantum cloning if information is carried by Hawking radiation. We thought we knew the answer: it takes too long to retrieve the information to then be able to jump into the black hole and discover the clone. This is probably true, but at that time we had no idea how close a call this might be.

It took until 2007 to properly formulate the problem. Patrick Hayden and John Preskill utterly surprised me, and probably everyone else who had been thinking about black holes, with their now-famous paper “Black Holes as Mirrors.” In a sense, this paper started a revolution in applying the powerful methods of quantum information theory to black holes.

We live in the age of entanglement. From quantum computing to condensed matter theory, to quantum gravity, entanglement is the new watchword. Preskill was in the vanguard of this revolution, but he was also the teacher who made the new concepts available to physicists like myself. We can now speak about entanglement, error correction, fault tolerance, tensor networks and more. The Preskill lectures were the indispensable source of knowledge and insight for us.

Congratulations John. And congratulations NAS.

-L. S.

Clocking in at a Cambridge conference

Posted on May 8, 2014 by Nicole Yunger Halpern

Science evolves on Facebook.

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

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

I almost replied, Are you sure?

Then I almost replied, Yes, please!

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

Trinity College, Cambridge.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The return of the superconducting high school teacher

Posted on May 5, 2014 by erynw

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

Posted on May 5, 2014 by smaloney61

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)

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.

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.

Because the interferometer is sensitive to changes in length of as little as 1X10^-15m, 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:

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/f_1550nm = 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^-10cm, 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/E_pulse= 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.

Hacking nature: loopholes in the laws of physics

Posted on April 29, 2014 by shaunmaguire

I spent my childhood hacking computers. When I was seven, my cousin showed up for Thanksgiving with a box filled with computer parts and we built my first computer. I got into competitive computer gaming around age eleven, and hacking was a natural extension of these activities. Then when I was sixteen, after doing poorly at a Counterstrike tournament, I decided that I should probably apply myself to other things. Needless to say, my parents were thrilled. So that’s when I bought my first computer (instead of building my own), which for deliberate but now antediluvian reasons was a Mac. A few years later, when I was taking CS 106 at Stanford, I was the first student in the course’s history whose reason for buying a Mac was “so that I couldn’t play computer games!” And now you know the story of my childhood.

The hacker mentality is quite different than the norm and my childhood trained me to look at absolutist laws as opportunities to find loopholes (of course only when legal and socially responsible!) I’ve applied this same mentality as I’ve been doing physics and I’d like to share with you some of the loopholes that I’ve gathered.

Scharnhorst effect enables light to travel faster than in vacuum (c=299,792,458 m/s): this is about the grandaddy of all laws, that nothing can travel faster than light in a vacuum! This effect is the most controversial on my list, because it hasn’t yet been experimentally verified, but it seems obvious with the right picture in mind. Most people’s mental model for light traveling in a vacuum is of little particles/waves called photons traveling through empty space. However, the vacuum is not empty! It is filled with pairs of virtual particles which momentarily fleet into existence. Interactions with these virtual particles create a small amount of ‘resistance’ as photons zoom through the vacuum (photons get absorbed into virtual electron-positron pairs and then spit back out as photons ad infinitum.) Thus, if we could somehow reduce the rate at which virtual particles are created, photons would interact less strongly with the vacuum, and would be able to travel marginally faster than c. But this is exactly what leads to the Casimir effect: the experimentally verified fact that if you take two mirrors and put them ~10 nanometers apart, then they will attract each other because there are more virtual particles created outside the cavity than inside [low momenta virtual modes are inaccessible because the uncertainty principle requires $\Delta x \cdot \Delta p= 10nm\cdot\Delta p \geq \hbar/2$ .] This effect is extremely small, only predicting that light would travel one part in $10^{36}$ faster than c. However, it should remind us all to deeply question assumptions.

This first loophole used quantum effects to beat a relativistic bound, but the next few loopholes are purely quantum, and are mainly related to that most quantum of all limits, the Heisenberg uncertainty principle.

Smashing the standard quantum limit (SQL) with squeezed measurements: the Heisenberg uncertainty principle tells us that there is a fundamental tradeoff in nature: the more precise your information about an object’s position, the less precise your knowledge about its momentum. Or vice versa, or replace x and p with E and t, or any other conjugate variables. This uncertainty principle is oftentimes written as $\Delta x\cdot \Delta p \geq \hbar/2$ . For a variety of reasons, in the early days of quantum mechanics, it was hard enough to imagine creating a state with $\Delta x \cdot \Delta p = \hbar/2$ , but there was some hope because this is obtained in the ground state of a quantum harmonic oscillator. In this case, we have $\Delta x = \Delta p = \sqrt{\hbar/2}$ . However, it was harder still to imagine creating states with $\Delta x < \sqrt{\hbar/2}$ , these states would be said to ‘go beyond the standard quantum limit’ (SQL). Over the intervening years, not only have we figured out how to go beyond the SQL using squeezed coherent states, but this is actually essential in some of our most exciting current experiments, like LIGO.

LIGO is an incredibly ambitious experiment which has been talked about multiple times on this blog. It is trying to usher in a new era of astronomy–moving beyond detecting photons–to detecting gravitational waves, ripples in spacetime which are generated as exceptionally massive objects merge, such as when two black holes collide. The effects of these waves on our local spacetime as they travel past earth are minuscule, on the scale of $10^{-18}m$ , which is about one thousand times shorter than the ‘diameter’ of a proton, and is the same order of magnitude as $\sqrt{\hbar/2}$ . Remarkably, LIGO has exploited squeezed light to demonstrate sensitivities beyond the SQL. LIGO expects to start detecting gravitational waves on a frequent basis as its upgrades deemed ‘advanced LIGO’ are completed over the next few years.

Compressed sensing beats Nyquist-Shannon: let’s play a game. Imagine I’m sending you a radio signal. How often do you need to measure the signal in order to be able to reconstruct it perfectly? The Nyquist-Shannon sampling theorem is a path-breaking result which Claude Shannon proved in 1949. If you measure at least twice as often as the highest frequency, then you are guaranteed perfect recovery of the signal. This incredibly profound result laid the foundation for modern communications. Also, it is important to realize that your signal can be much more general than simply radio waves, such as with a signal of images. This theorem is a sufficient condition for reconstruction, but is it necessary? Not even close. And it took us over 50 years to understand this in generality.

Compressed sensing was proposed between 2004-2006 by Emmanuel Candes, David Donaho and Terry Tao with important early contributions by Justin Romberg. I should note that Candes and Romberg were at Caltech during this period. The Nyquist-Shannon theorem told us that with a small amount of knowledge (a bound on the highest frequency) that we could reconstruct a signal perfectly by only measuring at a rate twice faster than the highest frequency–instead of needing to measure continuously. Compressed sensing says that with one extra assumption, assuming that only sparsely few of your frequencies are being used (call it 10 out of 1000), that you can recover your signal with high accuracy using dramatically fewer measurements. And it turns out that this assumption is valid for a huge range of applications: enabling real-time MRIs using conventional technology or more relevant to this blog, increasing our ability to distinguish quantum states via tomography.

Unlike the other topics in this blog post, I have never worked with compressed sensing, but my intuition goes like this: instead of measuring in the basis in which you are sparse (frequency for example), measure in a different basis. With high probability each of these measurements will pick up a little piece from each of the occupied modes. Then, to reconstruct your signal, you want to use the L0-“norm” to interpolate in such a way that you use the fewest frequency components possible. Computing the L0-“norm” is not efficient, so one of the major breakthroughs of compressed sensing was showing that with high probability computing the L1-norm approximates the L0 solution, and all of this can be done using a highly efficient linear program. However, I really shouldn’t be speculating because I’ve never invested much time into mastering this new tool, and I’m friends with a couple of the quantum state tomography authors, so maybe they’ll chime in?

Brahms is a cool dude. Brahms as a height map--cliffs=Gibbs phenomena=oh no! First three levels of Brahms wavelets.

Brahms is a cool dude. Brahms as a height map where cliffs=Gibbs phenomena=oh no! First three levels of Brahms as a Haar wavelet.

Wavelets as the mother of all bases: I previously wrote a post about the importance of choosing a convenient basis. Imagine you have an image which has a bunch of sharp contrasts, such as the outline of a person, or a horizon, or a table, basically anything. How do you store it efficiently? Due to the Gibbs phenomena, the Fourier basis is pretty awful for these applications. Here’s another motivating problem, imagine someone plays one note on an instrument. The sound is localized in both time and frequency. The Fourier basis is also pretty awful at storing/detecting this. Wavelets to the rescue! The theory of wavelets uses some beautiful math to solve the longstanding problem of finding a basis which is localized in both position and momenta space (or very close to it.) Wavelets have profound applications, some of my favorite include: modern image compression (JPEG 2000 onwards) is based on wavelets; Ingrid Daubechies and her colleagues used wavelets to detect forged paintings; recovering previously unrecoverable recordings of Brahms at the piano (I heard about this from Barry Simon, of Reed-Simon fame, who is currently teaching his last class ever); and even the FBI uses wavelets to compress images of fingerprints, obtaining a compression ratio of 20:1.

Postselection enables quantum cloning: the no-cloning theorem is well known in the field of quantum information. It says that you cannot find a machine (unitary operation U) which takes an arbitrary input state $|\psi\rangle$ , and a known state $|0\rangle$ , such that the machine maps $|\psi\rangle \otimes |0\rangle$ to $|\psi\rangle \otimes |\psi\rangle$ , and thereby cloning $|\psi \rangle$ . This is very easy to prove using the linearity of quantum mechanics. However, there are loopholes. One of the most trivial loopholes is realizing that one can take the state $|\psi\rangle$ and perform something called unambiguous state discrimination, which either spits out exactly which state $|\psi \rangle$ is with some probability, or otherwise spits out “I don’t know which state.” You can postselect that the unambigious state discrimination succeeded and prepare a unitary which clones the relevant states. Peter Shor has a comment on physics stackexchange describing this. Seth Lloyd and John Preskill outlined a less trivial version of this in their recent paper which tries to circumvent firewalls by using postselected quantum teleportation.

In this blog post, I’ve only described a tiny fraction of the quantum loopholes that have been discovered. If I had more space/time, two of the next examples I would describe are beating classical correlations with quantum entanglement, in order to win at CHSH games. I would also describe weak measurements and some of the peculiar things they lead to. Beyond that, I would probably refer you to Yakir Aharonov’s amazingly fun book about quantum paradoxes.

After reading this, I hope that the next time you encounter an inviolable law of nature, you’ll apply the hacker mentality and attempt to strip it down to its essence, isolate assumptions, and potentially find a loophole. But while you’re doing this, remember that you should never argue with your mother, or with mathematics!

A TED experience

Posted on April 21, 2014 by Jason Alicea

Around one year ago, I unexpectedly received an e-mail asking if I would speak at a local TEDx Youth event themed “Daring Discoveries”. I hadn’t attended a TEDx conference before (sadly I couldn’t make either of the previous ones held at Caltech). But I was familiar with the high-profile brand and so enthusiastically accepted the invitation. A few weeks ago, following a lot of preparation by the speakers and no doubt vastly more by the organizers, the event finally took place. On many levels it proved to be an unforgettable experience.

One thing that really struck me was that the conference was organized entirely by a team of local high school students. I find this truly remarkable, especially given the amount of work involved in putting together this sort of thing. (Finding speakers, fundraising, obtaining a venue, arranging innumerable technical logistics, putting together a webpage, sifting through applications, etc. I couldn’t imagine keeping track of all those details, much less at that stage!) The audience was also noteworthy: mostly other high school students from the area, their families, and other community members. In total there were about 100 participants. The vast majority reflected underrepresented groups in the sciences, which made it a particularly appealing outreach opportunity.

The organizers secured a venue at Puente Hills Mall in City of Industry. To get the mental juices flowing numerous classic brain teaser decorated the walls near the entrance. This one was my favorite:

This is an unusual paragraph. I’m curious how quickly you can find out what is so unusual about it. It looks so plain you would think nothing was wrong with it! In fact, nothing is wrong with it! It is unusual though. Study it, and think about it, but you still may not find anything odd. But if you work at it a bit, you might find out. Try to do so without any coaching.

Other interesting activities also awaited the participants, including a scavenger hunt and a “big ideas wall” where anyone could jot down ideas they viewed as worth spreading. It was fun reading what everyone had to say.

The list of speakers was eclectic and, among others, included a college student/entrepreneur, mathematicians, engineers, and educators. I found everyone’s talks absolutely riveting and felt really honored to be part of such an accomplished group. For my part I decided to tell a story about quantum computing—in particular the topological approach (what else?). Preparing was no easy task. I had to figure out a way to explain what quantum computers are, what they can do for us, why building one is hard, how “non-Abelian anyons” might one day prove to be the salvation, and why this direction is now looking increasingly promising. Of course without assuming any prior knowledge of quantum mechanics. And in about 15 minutes or so.

Given where we are in the quest for a quantum computer I had no choice but to conclude on a tentative yet optimistic note. I made sure though to convey what I think is an extremely important message. Namely, that the journey towards realizing quantum computing technology is as exciting—if not more so—than the finish line. That journey will undoubtedly be paved with groundbreaking discoveries that reveal spectacular new insights about how the universe works, forcing us to develop new physics paradigms along the way. It’s the prospect of such discoveries that energizes me to think about how we might achieve mastery over materials on large scales to hopefully overcome one of our generation’s greatest technological challenges. The Saturday Morning Breakfast Cereal comic below—which I very recently learned about from one of our colloquium speakers— perfectly encapsulates my view on the problem, both as a science advocate and a physicist working in the trenches. I thought showing this (censorship mine!) was a good message to leave the audience with.

Quantum Frontiers

A blog by the Institute for Quantum Information and Matter @ Caltech

“Feveral kinds of hairy mouldy fpots”

The theory of everything: Help wanted

Top 10 questions for your potential PhD adviser/group

John Preskill and the dawn of the entanglement frontier

Of magnetic monopoles and fast-scrambling black holes

Clocking in at a Cambridge conference

The return of the superconducting high school teacher

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

Hacking nature: loopholes in the laws of physics

A TED experience

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