Quantum

Three Common Misconceptions About Quantum Technology

dougfinke — Sat, 15 May 2021 20:19:10 +0000

We've seen an increasing number of misconceptions being spread about what quantum technology will be able to do. Admittedly, it is a complicated technology but we are concerned that overblown expectations can lead to a Quantum Winter or unwarranted investments being made in quantum technology due to misunderstandings. So in this article we are highlighting [...]

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German Government to Provide 2 Billion Euros ($2.4B USD) for Quantum Research and Development

dougfinke — Sat, 15 May 2021 01:24:06 +0000

Two German government ministries will fund quantum R&D for a total of almost €2 billion over a five year period. The Federal Ministry of Education and Research (BMBF) will contribute €1.1 billion and the Federal Ministry for Economic Affairs and Energy (BMWi) will contribute €878 million. Part of the funds will be allocated to developing a [...]

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Intel/QuTech Provide Test Results for Their Horse Ridge Cryogenic Quantum Control Chip

dougfinke — Fri, 14 May 2021 20:24:40 +0000

We previously reported on Intel's development of the Horse Ridge and Horse Ridge II cryogenic control chips that would allow generation of the necessary microwave pulses to control spin qubits at a temperature of 3 degrees kelvin right near the qubits themselves. This eliminates the requirement to route coaxial cables from external room temperature control [...]

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D-Wave and CINECA Announce a Collaboration to Offer Expanded Access to D-Wave’s Quantum Cloud Service to the Italian Scientific Community

dougfinke — Fri, 14 May 2021 18:51:24 +0000

D-Wave and CINECA, the Italian inter-university consortium and one of the world’s leading global supercomputing centers have announced a formal collaboration to offer Italian universities, researchers, and developers expanded access to practical quantum computing technology and resources through D-Wave’s Leap™ quantum cloud service. CINECA is an Italian consortium composed of 69 Italian Universities, 25 national research institutes [...]

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IBM Releases Qiskit Runtime for Private Beta

dougfinke — Fri, 14 May 2021 03:11:45 +0000

Back in February, we described a new capability that IBM was developing called Qiskit Runtime. This capability can be particularly useful for hybrid classical/quantum algorithms such as QAOA and VQE where data is passed back and forth between the classical and quantum computers multiple times. By co-locating the classical and the quantum computers together and [...]

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Quantum Delta NL Creates LightSpeed to Connect Dutch Quantum Startups with Investment Capital

dougfinke — Fri, 14 May 2021 00:12:25 +0000

Quite often the founders of a new quantum startup company may have come from an academic or technical background and may not have experience in raising capital or other commercial activities in running a business. In order to support Dutch quantum startup companies with scaling their business and fundraising Quantum Delta NL, a public-private partnership [...]

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New evidence for electron's dual nature found in a quantum spin liquid

Thu, 13 May 2021 16:39:51 +0000

New experiments provide evidence for a decades-old theory that, in the quantum regime, an electron behaves as if it is made of two particles: one particle that carries its negative charge and the other that gives it a magnet-like property called spin. The team detected evidence for this theory in materials called quantum spin liquids.

Quantum machine learning hits a limit

Thu, 13 May 2021 14:00:22 +0000

A black hole permanently scrambles information that can't be recovered with any quantum machine learning algorithm, shedding new light on the classic Hayden-Preskill thought experiment.

Funding Announcements (USD Equivalents): Arqit ($400M), ColdQuanta ($20M), Qnami ($4.4M), QphoX ($2.4M) and Agnostiq ($2M)

dougfinke — Thu, 13 May 2021 01:34:29 +0000

Arqit, a UK based company formed in 2017, will combine with Centricus Acquisition Corporation. The combined business will have a pro forma enterprise value of about $1 billion with $400 million of gross proceeds available for Arqit. Arqit has developed a product they call QuantumCloud which will allow organizations to exchange symmetric keys for encrypted [...]

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Low temperature physics gives insight into turbulence

Tue, 11 May 2021 12:11:44 +0000

A novel technique for studying vortices in quantum fluids has been developed by physicists. Turbulence in quantum systems, for example in superfluid helium 4, takes place on microscopic scales, and so far scientists have not had tools with sufficient precision to probe eddies this small. But now the team, working at temperature of a few thousandths of a degree above absolute zero, has harnessed nanoscience to allow the detection of single quantum vortices.

Testing quantum-secure communication in space

12011 — Tue, 11 May 2021 00:00:00 +0000

Tuesday, May 11, 2021

Researchers from Canada and the United Kingdom will test a new approach for secure communication using satellite-based quantum technology.

Chinese Team Develops a 62 Qubit Superconducting Processor

dougfinke — Mon, 10 May 2021 14:51:32 +0000

A Chinese research team from the University of Science and Technology of China has developed a programmable 62 qubit superconducting processor. The qubits are arranged in an 8x8 two dimensional configuration so it appears that only 62 out of the 64 qubits were operational. The team has been able to implement what they call Quantum [...]

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Light emitters for quantum circuits

Mon, 10 May 2021 14:44:20 +0000

The promise of a quantum internet depends on the complexities of harnessing light to transmit quantum information over fiber optic networks. A potential step forward was reported today by researchers who developed integrated chips that can generate light particles on demand and without the need for extreme refrigeration.

Three updates

Scott — Mon, 10 May 2021 05:47:52 +0000

For those who read my reply to Richard Borcherds on “teapot supremacy”: seeking better data, I ordered a dozen terra cotta flowerpots, and smashed eight of them on my driveway with my 4-year-old son, dropping each one from approximately 2 meters. For each flowerpot, we counted how many pieces it broke into, seeking insight about the distribution over that number. Unfortunately, it still proved nearly impossible to get good data, for a reason commenters had already warned me about: namely, there were typically 5-10 largeish shards, followed by “long tail” of smaller and smaller shards (eventually, just terra cotta specks), with no obvious place to draw the line and stop counting. Nevertheless, when I attempted to count only the shards that were “fingernail-length or larger,” here’s what I got: 1 pot with 9 shards, 1 with 11 shards, 2 with 13 shards, 2 with 15 shards, 1 with 17 shards, 1 with 19 shards. This is a beautiful (too beautiful?) symmetric distribution centered around a mean of 14 shards, although it’s anyone’s guess whether it approximates a Gaussian or something else. I have no idea why every pot broke into an odd number of shards, unless of course it was a 1-in-256-level fluke, or some cognitive bias that made me preferentially stop counting the shards at odd numbers.
Thanks so much to everyone who congratulated me for the ACM Prize, and especially those who (per my request) suggested charities to which to give bits of the proceeds! Tonight, after going through the complete list of suggestions, I made my first, but far from last, round of donations: $1000 each to the Deworm the World Initiative, GiveDirectly, the World Wildlife Fund, the Nature Conservancy, and Canada/USA Mathcamp (which had a huge impact on me when I attended it as a 15-year-old). One constraint, which might never arise in a decade of moral philosophy seminars, ended up being especially important in practice: if the donation form was confusing or buggy, or if it wouldn’t accept my donation without some onerous confirmation step involving a no-longer-in-use cellphone, then I simply moved on to the next charity.
Bobby Kleinberg asked me to advertise the call for nominations for the brand-new STOC Test of Time Award. The nomination deadline is coming up soon: May 24.

evolutionQ Introduces Quantum Delivery Network (QDN) to Help Extend QKD Networks

dougfinke — Sat, 08 May 2021 14:57:57 +0000

The software product from evolutionQ is called BasejumpQDN and is designed to help users overcome the limitations of QKD networks. Chief among these is the distance limitation inherent in fiber optic cables due to signal loss. While classical optical communications networks can solve this by installing classical repeaters every few hundred kilometers, the No Cloning [...]

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Atos and SENAI CIMATEC Form the Latin America Quantum Computing Center (LAQCC)

dougfinke — Sat, 08 May 2021 04:09:42 +0000

French multi-national information technology company Atos and Brazilian non-profit institution SENAI CIMATEC are teaming together to form the Latin America Quantum Computing Center (LAQCC), a center of excellence for quantum computing dedicated to the business sector. The center will promote adoption of quantum technologies, provide training for workforce development and encourage scientific research. The center [...]

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Evading the uncertainty principle in quantum physics

Thu, 06 May 2021 18:21:38 +0000

In quantum mechanics, the Heisenberg uncertainty principle dictates that the position and speed of an object cannot both be known fully precisely at the same time. Researchers now show that two vibrating drumheads, the size of a human hair, can be prepared in a quantum state which evades the uncertainty principle.

Quantum drum duet measured

Thu, 06 May 2021 18:20:46 +0000

Like conductors of a spooky symphony, researchers have 'entangled' two small mechanical drums and precisely measured their linked quantum properties. Entangled pairs like this might someday perform computations and transmit data in large-scale quantum networks.

New algorithm uses a hologram to control trapped ions

Wed, 05 May 2021 11:50:55 +0000

Researchers have discovered the most precise way to control individual ions using holographic optical engineering technology.

Complex shapes of photons to boost future quantum technologies

Tue, 04 May 2021 15:25:29 +0000

Researchers have demonstrated how two interfering photons can bunch into various shapes. These complex shapes are beneficial for quantum technologies, such as performing fast photonic quantum computations and safe data transfer. The method opens new possibilities also for creating enhanced measurement and sensing techniques.

IQC researchers honoured for excellence in scientific outreach

12011 — Mon, 03 May 2021 00:00:00 +0000

Monday, May 3, 2021

The David Johnston Award for Scientific Outreach recognizes students dedicated to promoting public awareness of quantum research and science in the community. IQC is proud to announce this year's recipients, PhD students Andrew Cameron and Connor Kapahi.

Blueprint for a robust quantum future

Thu, 29 Apr 2021 14:49:31 +0000

Researchers have established an invaluable resource for those looking to discover new quantum systems.

Mapping the electronic states in an exotic superconductor

Wed, 28 Apr 2021 17:30:03 +0000

Scientists mapped the electronic states in an exotic superconductor. The maps point to the composition range necessary for topological superconductivity, a state that could enable more robust quantum computing.

Scientists harness molecules into single quantum state

Wed, 28 Apr 2021 15:37:59 +0000

Being able to build and control systems of quantum particles, which are among the smallest objects in the universe, is the key to developing quantum technology. That goal is now a step closer thanks to scientists who just figured out how to bring multiple molecules at once into a single quantum state -- one of the most important goals in quantum physics.

A path to graphene topological qubits

Wed, 28 Apr 2021 15:37:21 +0000

Researchers demonstrate that magnetism and superconductivity can coexist in graphene, opening a pathway towards graphene-based topological qubits.

Researchers use a nanoscale synthetic antiferromagnet to toggle nonlinear spin dynamics

Wed, 28 Apr 2021 14:02:50 +0000

Researchers have used a nanoscale synthetic antiferromagnet to control the interaction between magnons -- research that could lead to faster and more energy-efficient computers.

Roadmap charts promising course for quantum nanotechnologies

12011 — Wed, 28 Apr 2021 00:00:00 +0000

Wednesday, April 28, 2021

More than sixty years after Richard Feynman delivered a seminal lecture that foreshadowed the development of nanotechnologies, Institute for Quantum Computing (IQC) and Department of Chemistry faculty member Jonathan Baugh and University of New South Wales Sydney faculty member Arne Laucht served as co-editors leading the publication of a roadmap that surveys major developments in the field of quantum nanotechnologies and explores exciting avenues for further development that will help usher in the next quantum revolution.

Silicon could be a photonics game-changer

Tue, 27 Apr 2021 17:55:18 +0000

New research has shown that silicon could be one of the most powerful materials for photonic informational manipulation - opening up new possibilities for the production of lasers and displays.

New two-dimensional material

Tue, 27 Apr 2021 13:48:25 +0000

An international team has discovered a previously unknown two-dimensional material by using modern high-pressure technology. The new material, beryllonitrene, consists of regularly arranged nitrogen and beryllium atoms. It has an unusual electronic lattice structure that shows great potential for applications in quantum technology.

The easiest exercise in the moral philosophy book

Scott — Sun, 25 Apr 2021 20:04:49 +0000

Peter Singer, in the parable that came to represent his whole worldview and that of the effective altruism movement more generally, asked us to imagine that we could save a drowning child at the cost of jumping into a lake and ruining an expensive new suit. Assuming we’d do that, he argued that we do in fact face an ethically equivalent choice; if we don’t donate most of our income to save children in the Third World, then we need to answer for why, as surely as the person who walked past the kid thrashing in the water.

In this post, I don’t want to take a position on Singer’s difficult but important hypothetical. I merely want to say: suppose that to save the child, you didn’t even have to jump in the water. Suppose you just had to toss a life preserver, one you weren’t using. Or suppose you just had to assure the child that it was OK to grab your life raft that was already in the water.

That, it seems, is the situation that the US and other rich countries will increasingly face with covid vaccines. What’s happening in India right now looks on track to become a humanitarian tragedy, if it isn’t already. Even if, as Indian friends tell me, this was a staggering failure of the Modi government, people shouldn’t pay for it with their lives. And we in the US now have tens of millions of vaccine doses sitting in warehouses unused, for regulatory and vaccine hesitancy reasons—stupidly, but we do. We’re past the time, in my opinion, when it’s morally obligatory either to use the doses or to give them away. Anyone in a position to manufacture more vaccines for distribution to poor countries, should also immediately get the intellectual property rights to do so.

I was glad to read, just this weekend, that the US is finally starting to move in the right direction. I hope it moves faster.

And I’m sorry that this brief post doesn’t contain any information or insight that you can’t find elsewhere. It just made me feel better to write it, is all.

Quantum steering for more precise measurements

Fri, 23 Apr 2021 12:57:05 +0000

Quantum systems consisting of several particles can be used to measure magnetic or electric fields more precisely. A young physicist has now proposed a new scheme for such measurements that uses a particular kind of correlation between quantum particles.

Doubts about teapot supremacy: my reply to Richard Borcherds

Scott — Tue, 20 Apr 2021 18:55:39 +0000

Richard Borcherds is a British mathematician at Berkeley, who won the 1998 Fields Medal for the proof of the monstrous moonshine conjecture among many other contributions. A couple months ago, Borcherds posted on YouTube a self-described “rant” about quantum computing, which was recently making the rounds on Facebook and which I found highly entertaining.

Borcherds points out that the term “quantum supremacy” means only that quantum computers can outperform existing classical computers on some benchmark, which can be chosen to show maximum advantage for the quantum computer. He allows that BosonSampling could have some value, for example in calibrating quantum computers or in comparing one quantum computer to another, but he decries the popular conflation of quantum supremacy with the actual construction of a scalable quantum computer able (for example) to run Shor’s algorithm to break RSA.

Borcherds also proposes a “teapot test,” according to which any claim about quantum computers can be dismissed if an analogous claim would hold for a teapot (which he brandishes for the camera). For example, there are many claims to solve practical optimization and machine learning problems by “quantum/classical hybrid algorithms,” wherein a classical computer does most of the work but a quantum computer is somehow involved. Borcherds points out that, at least as things stand in early 2021, in most or all such cases, the classical computer could’ve probably done as well entirely on its own. So then if you put a teapot on top of your classical computer while it ran, you could equally say you used a “classical/teapot hybrid approach.”

Needless to say, Borcherds is correct about all of this. I’ve made similar points on this blog for 15 years, although less Britishly. I’m delighted to have such serious new firepower on the scoffing-at-QC-hype team.

I do, however, have one substantive disagreement. At one point, Borcherds argues that sampling-based quantum supremacy itself fails his teapot test. For consider the computational problem of predicting how many pieces a teapot will break into if it’s dropped on the ground. Clearly, he says, the teapot itself will outperform any simulation running on any existing classical computer at that task, and will therefore achieve “teapot supremacy.” But who cares??

I’m glad that Borcherds has set out, rather crisply, an objection that’s been put to me many times over the past decade. The response is simple: I don’t believe the teapot really does achieve teapot supremacy on the stated task! At the least, I’d need to be shown why. You can’t just assert it without serious argument.

If we want to mirror the existing quantum supremacy experiments, then the teapot computational problem, properly formulated, should be: given as input a description of a teapot’s construction, the height from which it’s dropped, etc., output a sample from the probability distribution over the number of shards that the teapot will break into when it hits the floor.

If so, though, then clearly a classical computer can easily sample from the same distribution! Why? Because presumably we agree that there’s a negligible probability of more than (say) 1000 shards. So the distribution is characterized by a list of at most 1000 probabilities, which can be estimated empirically (at the cost of a small warehouse of smashed teapots) and thereafter used to generate samples. In the plausible event that the distribution is (say) a Gaussian, it’s even easier: just estimate the mean and variance.

A couple days ago, I was curious what the distribution looked like, so I decided to order some teapots from Amazon and check. Unfortunately, real porcelain teapots are expensive, and it seemed vaguely horrific to order dozens (as would be needed to get reasonable data) for the sole purpose of smashing them on my driveway. So I hit on what seemed like a perfect solution: I ordered toy teapots, which were much smaller and cheaper. Alas, when my toy “porcelain” teapots arrived yesterday, they turned out (unsurprisingly in retrospect for a children’s toy) to be some sort of plastic or composite material, meaning that they didn’t break unless one propelled them downward forcefully. So, while I can report that they tended to break into one or two large pieces along with two or three smaller shards, I found it impossible to get better data. (There’s a reason why I became a theoretical computer scientist…)

The good news is that my 4-year-old son had an absolute blast smashing toy teapots with me on our driveway, while my 8-year-old daughter was thrilled to take the remaining, unbroken teapots for her dollhouse. I apologize if this fails to defy gender stereotypes.

Anyway, it might be retorted that it’s not good enough to sample from a probability distribution: what’s wanted, rather, is to calculate how many pieces this specific teapot will break into, given all the microscopic details of it and its environment. Aha, this brings us to a crucial conceptual point: in order for something to count as an “input” to a computer, you need to be able to set it freely. Certainly, at the least, you need to be able to measure and record the input in its entirety, so that someone trying to reproduce your computation on a standard silicon computer would know exactly which computation to do. You don’t get to claim computational supremacy based on a problem with secret inputs: that’s like failing someone on a math test without having fully told them the problems.

Ability to set and know the inputs is the key property that’s satisfied by Google’s quantum supremacy experiment, and to a lesser extent by the USTC BosonSampling experiment, but that’s not satisfied at all by the “smash a teapot on the floor” experiment. Or perhaps it’s better to say: influences on a computation that vary uncontrollably and chaotically, like gusts of air hitting the teapot as it falls to the floor, shouldn’t be called “inputs” at all; they’re simply noise sources. And what one does with noise sources is to try to estimate their distribution and average over them—but in that case, as I said, there’s no teapot supremacy.

A Facebook friend said to me: that’s well and good, but surely we could change Borcherds’s teapot experiment to address this worry? For example: add a computer-controlled lathe (or even a 3D printer), with which you can build a teapot in an arbitrary shape of your choice. Then consider the problem of sampling from the probability distribution over how many pieces that teapot will smash into, when it’s dropped from some standard height onto some standard surface. I replied that this is indeed more interesting—in fact, it already seems more like what engineers do in practice (still, sometimes!) when building wind tunnels, than like a silly reductio ad absurdum of quantum supremacy experiments. On the other hand, if you believe the Extended Church-Turing Thesis, then as long as your analog computer is governed by classical physics, it’s presumably inherently limited to an Avogadro’s number type speedup over a standard digital computer, whereas with a quantum computer, you’re limited only by the exponential dimensionality of Hilbert space, which seems more interesting.

Or maybe I’m wrong—in which case, I look forward to the first practical demonstration of teapot supremacy! Just like with quantum supremacy, though, it’s not enough to assert it; you need to … put the tea where your mouth is.

Combining light, superconductors could boost AI capabilities

Tue, 20 Apr 2021 17:10:57 +0000

As artificial intelligence has attracted interest, researchers are focused on understanding how the brain accomplishes cognition so they can construct systems with general intelligence comparable to humans' intelligence. Researchers propose an approach to AI that focuses on integrating photonic components with superconducting electronics; using light for communication and complex electronic circuits for computation could enable artificial cognitive systems of scale and functionality beyond what can be achieved with either light or electronics alone.

Boosting fiber optics communications with advanced quantum-enhanced receiver

Tue, 20 Apr 2021 17:10:51 +0000

Fiber optic technology is the holy grail of high-speed, long-distance telecommunications. Still, with the continuing exponential growth of internet traffic, researchers are warning of a capacity crunch. Researchers show how quantum-enhanced receivers could play a critical role in addressing this challenge. The scientists developed a method to enhance receivers based on quantum physics properties to dramatically increase network performance while significantly reducing the error bit rate and energy consumption.

Seed fund continues to support new diverse quantum projects

12574 — Tue, 20 Apr 2021 00:00:00 +0000

Tuesday, April 20, 2021

Two projects most recently supported by the Quantum Quest Seed Fund (QQSF) aim to make quantum concepts more easily understood. The goal of one project is to explain how differences in cultural background influence perception and acceptance to the basic principles of quantum physics, while the other aims to use interactive digital storytelling to advance quantum literacy.

Materials advances are key to development of quantum hardware

Mon, 19 Apr 2021 17:57:06 +0000

A new article argues that the ability to move forward on developing useful quantum computers requires new major advances in materials science, engineering and fabrication. The authors call for new approaches from broad areas of science and engineering.

Federal government launches national quantum strategy

12011 — Mon, 19 Apr 2021 00:00:00 +0000

Monday, April 19, 2021

The University of Waterloo’s Institute for Quantum Computing welcomes the federal budget commitment to investing in a national quantum strategy.

Alongside industry partners and other Canadian universities, the University of Waterloo has been advocating for a national quantum strategy to maintain Canada’s competitive edge as we develop and commercialize tomorrow’s technological breakthroughs, and train the workforce needed to bring these discoveries to market.

Experiments cast doubts on the existence of quantum spin liquids

Fri, 16 Apr 2021 16:00:08 +0000

A quantum spin liquid is a state of matter in which interacting quantum spins do not align even at lowest temperatures, but remain disordered. Research on this state has been going on for almost 50 years, but whether it really exists has never been proven beyond doubt. An international team has now put an end to the dream of a quantum spin liquid for the time being. Nevertheless, the matter remains exciting.

Entanglement-based quantum network

Thu, 15 Apr 2021 18:26:19 +0000

A team of researchers reports realization of a multi-node quantum network, connecting three quantum processors. In addition, they achieved a proof-of-principle demonstration of key quantum network protocols.

The ACM Prize thing

Scott — Wed, 14 Apr 2021 15:41:51 +0000

Last week I got an email from Dina Katabi, my former MIT colleague, asking me to call her urgently. Am I in trouble? For what, though?? I haven’t even worked at MIT for five years!

Luckily, Dina only wanted to tell me that I’d been selected to receive the 2020 ACM Prize in Computing, a mid-career award founded in 2007 that comes with $250,000 from Infosys. Not the Turing Award but I’d happily take it! And I could even look back on 2020 fondly for something.

I was utterly humbled to see the list of past ACM Prize recipients, which includes amazing computer scientists I’ve been privileged to know and learn from (like Jon Kleinberg, Sanjeev Arora, and Dan Boneh) and others who I’ve admired from afar (like Daphne Koller, Jeff Dean and Sanjay Ghemawat of Google MapReduce, and David Silver of AlphaGo and AlphaZero).

I was even more humbled, later, to read my prize citation, which focuses on four things:

The theoretical foundations of the sampling-based quantum supremacy experiments now being carried out (and in particular, my and Alex Arkhipov’s 2011 paper on BosonSampling);
My and Avi Wigderson’s 2008 paper on the algebrization barrier in complexity theory;
Work on the limitations of quantum computers (in particular, the 2002 quantum lower bound for the collision problem); and
Public outreach about quantum computing, including through QCSD, popular talks and articles, and this blog.

I don’t know if I’m worthy of such a prize—but I know that if I am, then it’s mainly for work I did between roughly 2001 and 2012. This honor inspires me to want to be more like I was back then, when I was driven, non-jaded, and obsessed with figuring out the contours of BQP and efficient computation in the physical universe. It makes me want to justify the ACM’s faith in me.

I’m grateful to the committee and nominators, and more broadly, to the whole quantum computing and theoretical computer science communities—which I “joined” in some sense around age 16, and which were the first communities where I ever felt like I belonged. I’m grateful to the mentors who made me what I am, especially Chris Lynch, Bart Selman, Lov Grover, Umesh Vazirani, Avi Wigderson, and (if he’ll allow me to include him) John Preskill. I’m grateful to the slightly older quantum computer scientists who I looked up to and tried to emulate, like Dorit Aharonov, Andris Ambainis, Ronald de Wolf, and John Watrous. I’m grateful to my wonderful colleagues at UT Austin, in the CS department and beyond. I’m grateful to my students and postdocs, the pride of my professional life. I’m grateful, of course, to my wife, parents, and kids.

By coincidence, my last post was also about prizes to theoretical computer scientists—in that case, two prizes that attracted controversy because of the recipient’s (or would-be recipient’s) political actions or views. It would understate matters to point out that not everyone has always agreed with everything I’ve said on this blog. I’m ridiculously lucky, and I know it, that even living through this polarized and tumultuous era, I never felt forced to choose between academic success and the freedom to speak my conscience in public under my real name. If there’s been one constant in my public stands, I’d like to think that—inspired by memories of my own years as an unknown, awkward, self-conscious teenager—it’s been my determination to nurture and protect talented young scientists, whatever they look like and wherever they come from. And I’ve tried to live up to that ideal in real life, and I welcome anyone’s scrutiny as to how well I’ve done.

What should I do with the prize money? I confess that my first instinct was to donate it, in its after-tax entirety, to some suitable charity—specifically, something that would make all the strangers who’ve attacked me on Twitter, Reddit, and so forth over the years realize that I’m fundamentally a good person. But I was talked out of this plan by my family, who pointed out that
(1) in all likelihood, nothing will make online strangers stop hating me,
(2) in any case this seems like a poor basis for making decisions, and
(3) if I really want to give others a say in what to do with the winnings, then why not everyone who’s stood by me and supported me?

So, beloved commenters! Please mention your favorite charitable causes below, especially weird ones that I wouldn’t have heard of otherwise. If I support their values, I’ll make a small donation from my prize winnings. Or a larger donation, especially if you donate yourself and challenge me to match. Whatever’s left after I get tired of donating will probably go to my kids’ college fund.

Water and quantum magnets share critical physics

Wed, 14 Apr 2021 15:32:42 +0000

Water can freeze from liquid to solid ice or boil into a gas. In the kitchen these 'phase transitions' aren't smooth, but their discontinuous nature is smoothed out at high pressure. An international team of physicists has now discovered the same behavior in certain quantum magnets, which may have consequences for the technology of qubits.

New method for putting quantum correlations to the test

Tue, 13 Apr 2021 16:10:05 +0000

An international team of physicists has identified a new technique for testing the quality of quantum correlations. Quantum computers run their algorithms on large quantum systems by creating quantum correlations across all of them. It is important to verify the quantum correlations achieved are of the desired quality. However, carrying out checks is resource-intensive so the team has proposed a new technique that significantly reduces the number of measurements while increasing the resilience against noise.

A molecule that responds to light

Tue, 13 Apr 2021 15:06:23 +0000

Light can be used to operate quantum information processing systems, e.g. quantum computers, quickly and efficiently. Researchers have now significantly advanced the development of molecule-based materials suitable for use as light-addressable fundamental quantum units. They have demonstrated for the first time the possibility of addressing nuclear spin levels of a molecular complex of europium(III) rare-earth ions with light.

Just some prizes

Scott — Fri, 09 Apr 2021 18:15:33 +0000

Oded Goldreich is a theoretical computer scientist at the Weizmann Institute in Rehovot, Israel. He’s best known for helping to lay the rigorous foundations of cryptography in the 1980s, through seminal results like the Goldreich-Levin Theorem (every one-way function can be modified to have a hard-core predicate), the Goldreich-Goldwasser-Micali Theorem (every pseudorandom generator can be made into a pseudorandom function), and the Goldreich-Micali-Wigderson protocol for secure multi-party computation. I first met Oded more than 20 years ago, when he lectured at a summer school at the Institute for Advanced Study in Princeton, barefoot and wearing a tank top and what looked like pajama pants. It was a bracing introduction to complexity-theoretic cryptography. Since then, I’ve interacted with Oded from time to time, partly around his firm belief that quantum computing is impossible.

Last month a committee in Israel voted to award Goldreich the Israel Prize (roughly analogous to the US National Medal of Science), for which I’d say Goldreich had been a plausible candidate for decades. But alas, Yoav Gallant, Netanyahu’s Education Minister, then rather non-gallantly blocked the award, solely because he objected to Goldreich’s far-left political views (and apparently because of various statements Goldreich signed, including in support of a boycott of Ariel University, which is in the West Bank). The case went all the way to the Israeli Supreme Court (!), which ruled two days ago in Gallant’s favor: he gets to “delay” the award to investigate the matter further, and in the meantime has apparently sent out invitations for an award ceremony next week that doesn’t include Goldreich. Some are now calling for the other winners to boycott the prize in solidarity until this is righted.

I doubt readers of this blog need convincing that this is a travesty and an embarrassment, a shanda, for the Netanyahu government itself. That I disagree with Goldreich’s far-left views (or might disagree, if I knew in any detail what they were) is totally immaterial to that judgment. In my opinion, not even Goldreich’s belief in the impossibility of quantum computers should affect his eligibility for the prize. Quantum computing promises to harness the strange properties of quantum mechanics in machines that will outperform even the most powerful supercomputers of today. But the extent of their application, it turns out, isn’t entirely clear.

To fully realize the potential of quantum computing, scientists must start with the basics: developing step-by-step procedures, or algorithms, for quantum computers to perform simple tasks, like the factoring of a number. These simple algorithms can then be used as building blocks for more complicated calculations.

Prasanth Shyamsundar, a postdoctoral research associate at the Department of Energy’s Fermilab Quantum Institute, has done just that. In a preprint paper released in February, he announced two new algorithms that build upon existing work in the field to further diversify the types of problems quantum computers can solve.

“There are specific tasks that can be done faster using quantum computers, and I’m interested in understanding what those are,” Shyamsundar said. “These new algorithms perform generic tasks, and I am hoping they will inspire people to design even more algorithms around them.”

Shyamsundar’s quantum algorithms, in particular, are useful when searching for a specific entry in an unsorted collection of data. Consider a toy example: Suppose we have a stack of 100 vinyl records, and we task a computer with finding the one jazz album in the stack.

Classically, a computer would need to examine each individual record and make a yes-or-no decision about whether it is the album we are searching for, based on a given set of search criteria.

“You have a query, and the computer gives you an output,” Shyamsundar said. “In this case, the query is: Does this record satisfy my set of criteria? And the output is yes or no.”

Finding the record in question could take only a few queries if it is near the top of the stack, or closer to 100 queries if the record is near the bottom. On average, a classical computer would locate the correct record with 50 queries, or half the total number in the stack.

A quantum computer, on the other hand, would locate the jazz album much faster. This is because it has the ability to analyze all of the records at once, using a quantum effect called superposition.

With this property, the number of queries needed to locate the jazz album is only about 10, the square root of the number of records in the stack. This phenomenon is known as quantum speedup and is a result of the unique way quantum computers store information.

The quantum advantage

Classical computers use units of storage called bits to save and analyze data. A bit can be assigned one of two values: 0 or 1.

The quantum version of this is called a qubit. Qubits can be either 0 or 1 as well, but unlike their classical counterparts, they can also be a combination of both values at the same time. This is known as superposition, and allows quantum computers to assess multiple records, or states, simultaneously.

Qubits can be in a superposition of 0 and 1, while classical bits can be only one or the other. Image: Jerald Pinson

“If a single qubit can be in a superposition of 0 and 1, that means two qubits can be in a superposition of four possible states,” Shyamsundar said. The number of accessible states grows exponentially with the number of qubits used.

Seems powerful, right? It’s a huge advantage when approaching problems that require extensive computing power. The downside, however, is that superpositions are probabilistic in nature — meaning they won’t yield definite outputs about the individual states themselves.

Think of it like a coin flip. When in the air, the state of the coin is indeterminate; it has a 50% probability of landing either heads or tails. Only when the coin reaches the ground does it settle into a value that can be determined precisely.

Quantum superpositions work in a similar way. They’re a combination of individual states, each with their own probability of showing up when measured.

But the process of measuring won’t necessarily collapse the superposition into the value we are looking for. That depends on the probability associated with the correct state.

“If we create a superposition of records and measure it, we’re not necessarily going to get the right answer,” Shyamsundar said. “It’s just going to give us one of the records.”

To fully capitalize on the speedup quantum computers provide, then, scientists must somehow be able to extract the correct record they are looking for. If they cannot, the advantage over classical computers is lost.

Amplifying the probabilities of correct states

Luckily, scientists developed an algorithm nearly 25 years ago that will perform a series of operations on a superposition to amplify the probabilities of certain individual states and suppress others, depending on a given set of search criteria. That means when it comes time to measure, the superposition will most likely collapse into the state they are searching for.

But the limitation of this algorithm is that it can be applied only to Boolean situations, or ones that can be queried with a yes or no output, like searching for a jazz album in a stack of several records.

A quantum computer can amplify the probabilities of certain individual records and suppress others, as indicated by the size and color of the disks in the output superposition. Standard techniques are able to assess only Boolean scenarios, or ones that can be answered with a yes or no output. Illustration: Prasanth Shyamsundar

Scenarios with non-Boolean outputs present a challenge. Music genres aren’t precisely defined, so a better approach to the jazz record problem might be to ask the computer to rate the albums by how “jazzy” they are. This could look like assigning each record a score on a scale from 1 to 10.

New amplification algorithms expand the utility of quantum computers to handle non-Boolean scenarios, allowing for an extended range of values to characterize individual records, such as the scores assigned to each disk in the output superposition above. Illustration: Prasanth Shyamsundar

Previously, scientists would have to convert non-Boolean problems such as this into ones with Boolean outputs.

“You’d set a threshold and say any state below this threshold is bad, and any state above this threshold is good,” Shyamsundar said. In our jazz record example, that would be the equivalent of saying anything rated between 1 and 5 isn’t jazz, while anything between 5 and 10 is.

But Shyamsundar has extended this computation such that a Boolean conversion is no longer necessary. He calls this new technique the non-Boolean quantum amplitude amplification algorithm.

“If a problem requires a yes-or-no answer, the new algorithm is identical to the previous one,” Shyamsundar said. “But this now becomes open to more tasks; there are a lot of problems that can be solved more naturally in terms of a score rather than a yes-or-no output.”

A second algorithm introduced in the paper, dubbed the quantum mean estimation algorithm, allows scientists to estimate the average rating of all the records. In other words, it can assess how “jazzy” the stack is as a whole.

Both algorithms do away with having to reduce scenarios into computations with only two types of output, and instead allow for a range of outputs to more accurately characterize information with a quantum speedup over classical computing methods.

Procedures like these may seem primitive and abstract, but they build an essential foundation for more complex and useful tasks in the quantum future. Within physics, the newly introduced algorithms may eventually allow scientists to reach target sensitivities faster in certain experiments. Shyamsundar is also planning to leverage these algorithms for use in quantum machine learning.

And outside the realm of science? The possibilities are yet to be discovered.

“We’re still in the early days of quantum computing,” Shyamsundar said, noting that curiosity often drives innovation. “These algorithms are going to have an impact on how we use quantum computers in the future.”

This work is supported by the Department of Energy’s Office of Science Office of High Energy Physics QuantISED program.

The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit science.energy.gov.

The Computational Expressiveness of a Model Train Set: A Paperlet

Scott — Sun, 04 Apr 2021 18:37:49 +0000

My son Daniel had his fourth birthday a couple weeks ago. For a present, he got an electric train set. (For completeness—and since the details of the train set will be rather important to the post—it’s called “WESPREX Create a Dinosaur Track”, but this is not an ad and I’m not getting a kickback for it.)

As you can see, the main feature of this set is a Y-shaped junction, which has a flap that can control which direction the train goes. The logic is as follows:

If the train is coming up from the “bottom” of the Y, then it continues to either the left arm or the right arm, depending on where the flap is. It leaves the flap as it was.

If the train is coming down the left or right arms of the Y, then it continues to the bottom of the Y, pushing the flap out of its way if it’s in the way. (Thus, if the train were ever to return to this Y-junction coming up from the bottom, not having passed the junction in the interim, it would necessarily go to the same arm, left or right, that it came down from.)

The train set also comes with bridges and tunnels; thus, there’s no restriction of planarity. Finally, the train set comes with little gadgets that can reverse the train’s direction, sending it back in the direction that it came from:

These gadgets don’t seem particularly important, though, since we could always replace them if we wanted by a Y-junction together with a loop.

Notice that, at each Y-junction, the position of the flap stores one bit of internal state, and that the train can both “read” and “write” these bits as it moves around. Thus, a question naturally arises: can this train set do any nontrivial computations? If there are n Y-junctions, then can it cycle through exp(n) different states? Could it even solve PSPACE-complete problems, if we let it run for exponential time? (For a very different example of a model-train-like system that, as it turns out, is able to express PSPACE-complete problems, see this recent paper by Erik Demaine et al.)

Whatever the answers regarding Daniel’s train set, I knew immediately on watching the thing go that I’d have to write a “paperlet” on the problem and publish it on my blog (no, I don’t inflict such things on journals!). Today’s post constitutes my third “paperlet,” on the general theme of a discrete dynamical system that someone showed me in real life (e.g. in a children’s toy or in biology) having more structure and regularity than one might naïvely expect. My first such paperlet, from 2014, was on a 1960s toy called the Digi-Comp II; my second, from 2016, was on DNA strings acted on by recombinase (OK, that one was associated with a paper in Science, but my combinatorial analysis wasn’t the main point of the paper).

Anyway, after spending an enjoyable evening on the problem of Daniel’s train set, I was able to prove that, alas, the possible behaviors are quite limited (I classified them all), falling far short of computational universality.

If you feel like I’m wasting your time with trivialities (or if you simply enjoy puzzles), then before you read any further, I encourage you to stop and try to prove this for yourself!

Back yet? OK then…

Theorem: Assume a finite amount of train track. Then after a linear amount of time, the train will necessarily enter a “boring infinite loop”—i.e., an attractor state in which at most two of the flaps keep getting toggled, and the rest of the flaps are fixed in place. In more detail, the attractor must take one of four forms:

I. a line (with reversing gadgets on both ends),
II. a simple cycle,
III. a “lollipop” (with one reversing gadget and one flap that keeps getting toggled), or
IV. a “dumbbell” (with two flaps that keep getting toggled).

In more detail still, there are seven possible topologically distinct trajectories for the train, as shown in the figure below.

Here the red paths represent the attractors, where the train loops around and around for an unlimited amount of time, while the blue paths represent “runways” where the train spends a limited amount of time on its way into the attractor. Every degree-3 vertex is assumed to have a Y-junction, while every degree-1 vertex is assumed to have a reversing gadget, unless (in IIb) the train starts at that vertex and never returns to it.

The proof of the theorem rests on two simple observations.

Observation 1: While the Y-junctions correspond to vertices of degree 3, there are no vertices of degree 4 or higher. This means that, if the train ever revisits a vertex v (other than the start vertex) for a second time, then there must be some edge e incident to v that it also traverses for a second time immediately afterward.

Observation 2: Suppose the train traverses some edge e, then goes around a simple cycle (meaning, one where no edges or vertices are reused), and then traverses e again, going in the same direction as the first time. Then from that point forward, the train will just continue around the same simple cycle forever.

The proof of Observation 2 is simply that, if there were any flap that might be in the train’s way as it continued around the simple cycle, then the train would already have pushed it out of the way its first time around the cycle, and nothing that happened thereafter could possibly change the flap’s position.

Using the two observations above, let’s now prove the theorem. Let the train start where it will, and follow it as it traces out a path. Since the graph is finite, at some point some already-traversed edge must be traversed a second time. Let e be the first such edge. By Observation 1, this will also be the first time the train’s path intersects itself at all. There are then three cases:

Case 1: The train traverses e in the same direction as it did the first time. By Observation 2, the train is now stuck in a simple cycle forever after. So the only question is what the train could’ve done before entering the simple cycle. We claim that at most, it could’ve traversed a simple path. For otherwise, we’d contradict the assumption that e was the first edge that the train visited twice on its journey. So the trajectory must have type IIa, IIb, or IIc in the figure.

Case 2: Immediately after traversing e, the train hits a reversing gadget and traverses e again the other way. In this case, the train will clearly retrace its entire path and then continue past its starting point; the question is what happens next. If it hits another reversing gadget, then the trajectory will have type I in the figure. If it enters a simple cycle and stays in it, then the trajectory will have type IIb in the figure. If, finally, it makes a simple cycle and then exits the cycle, then the trajectory will have type III in the figure. In this last case, the train’s trajectory will form a “lollipop” shape. Note that there must be a Y-junction where the “stick” of the lollipop meets the “candy” (i.e., the simple cycle), with the base of the Y aligned with the stick (since otherwise the train would’ve continued around and around the candy). From this, we deduce that every time the train goes around the candy, it does so in a different orientation (clockwise or counterclockwise) than the time before; and that the train toggles the Y-junction’s flap every time it exits the candy (although not when it enters the candy).

Case 3: At some point after traversing e in the forward direction (but not immediately after), the train traverses e in the reverse direction. In this case, the broad picture is analogous to Case 2. So far, the train has made a lollipop with a Y-junction connecting the stick to the candy (i.e. cycle), the base of the Y aligned with the stick, and e at the very top of the stick. The question is what happens next. If the train next hits a reversing gadget, the trajectory will have type III in the figure. If it enters a new simple cycle, disjoint from the first cycle, and never leaves it, the trajectory will have type IId in the figure. If it enters a new simple cycle, disjoint from the first cycle, and does leave it, then the trajectory now has a “dumbbell” pattern, type IV in the figure (also shown in the first video). There’s only one last situation to worry about: namely, that the train makes a new cycle that intersects the first cycle, forming a “theta” (θ) shaped trajectory. In this case, there must be a Y-junction at the point where the new cycle bumps into the old cycle. Now, if the base of the Y isn’t part of the old cycle, then the train never could’ve made it all the way around the old cycle in the first place (it would’ve exited the old cycle at this Y-junction), contradiction. If the base of the Y is part of the old cycle, then the flap must have been initially set to let the train make it all the way around the old cycle; when the train then reenters the old cycle, the flap must be moved so that the train will never make it all the way around the old cycle again. So now the train is stuck in a new simple cycle (sharing some edges with the old cycle), and the trajectory has type IIc in the figure.

This completes the proof of the theorem.

We might wonder: why isn’t this model train set capable of universal computation, of AND, OR, and NOT gates—or at any rate, of some computation more interesting than repeatedly toggling one or two flaps? My answer might sound tautological: it’s simply that the logic of the Y-junctions is too limited. Yes, the flaps can get pushed out of the way—that’s a “bit flip”—but every time such a flip happens, it helps to set up a “groove” in which the train just wants to continue around and around forever, not flipping any additional bits, with only the minor complications of the lollipop and dumbbell structures to deal with. Even though my proof of the theorem might’ve seemed like a tedious case analysis, it had this as its unifying message.

It’s interesting to think about what gadgets would need to be added to the train set to make it computationally universal, or at least expressively richer—able, as turned out to be the case for the Digi-Comp II, to express some nontrivial complexity class falling short of P. So for example, what if we had degree-4 vertices, with little turnstile gadgets? Or multiple trains, which could be synchronized to the millisecond to control how they interacted with each other via the flaps, or which could even crash into each other? I look forward to reading your ideas in the comment section!

For the truth is this: quantum complexity classes, BosonSampling, closed timelike curves, circuit complexity in black holes and AdS/CFT, etc. etc.—all these topics are great, but the same models and problems do get stale after a while. I aspire for my research agenda to chug forward, full steam ahead, into new computational domains.

PS. Happy Easter to those who celebrate!

Qubits composed of holes could be the trick to build faster, larger quantum computers

Fri, 02 Apr 2021 13:59:46 +0000

A new study demonstrates a path towards scaling individual qubits to a mini-quantum computer, using holes. The study identifies a 'sweet spot' where the qubit is least sensitive to noise (ensuring longer retention of information) and simultaneously can be operated the fastest.

Study shows promise of quantum computing using factory-made silicon chips

Wed, 31 Mar 2021 17:09:05 +0000

For the study, researchers were able to isolate and measure the quantum state of a single electron (the qubit) in a silicon transistor manufactured using a 'CMOS' technology similar to that used to make chips in computer processors.