Quantum

NTT Research to Collaborate with Caltech to Develop the World’s Fastest Coherent Ising Machines

dougfinke1 — Wed, 27 Jan 2021 01:22:21 +0000

One of the alternate approaches to gate level quantum computers is the Coherent Ising Machine (CIM). These are also sometimes called Quantum Neural Networks. A Coherent Ising Machine is similar to the D-Wave quantum annealer in that it is designed to solve combinatorial optimization problems, but it is different because it uses optical fiber loops, [...]

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Research Roundup for January 2021

dougfinke1 — Tue, 26 Jan 2021 00:07:05 +0000

Shown below are summaries of a few interesting research papers related to quantum computing that have been published over the past month. Title: Model-free readout-error mitigation for quantum expectation valuesOrganization: IBMThe paper proposes an efficient way to mitigate the readout errors that occur when the final measurements of a quantum computation are Pauli measurements. Simulations [...]

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Riverlane Closes a $20 Million Series A Investment Round

dougfinke1 — Mon, 25 Jan 2021 19:29:50 +0000

The round was led by Draper Esprit with additional participation from Cambridge Innovation Capital, Amadeus Capital Partners, and Cambridge Enterprise, University of Cambridge. Riverlane is developing a quantum operating system called Deltaflow and they indicate that 20% of the world's quantum hardware manufactures have already signed up to use it. The Series A funding follows a £3.25 million [...]

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Adding or subtracting single quanta of sound

Mon, 25 Jan 2021 16:23:08 +0000

Researchers perform experiments that can add or subtract a single quantum of sound -- with surprising results when applied to noisy sound fields.

If You Think the Quantum Race is Only Between the U.S. and China, Think Again

dougfinke1 — Sat, 23 Jan 2021 22:10:31 +0000

There have recently been a number articles in the mainstream press that would lead one to the conclusion that the quantum race is limited to the U.S. versus China. (See here, here, and here). These articles are ignoring that tremendous impact that Europe will have in the development and implementation of quantum technologies. To start, [...]

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Oxford Instruments Announces Two Dilution Refrigerator Design Wins

dougfinke1 — Fri, 22 Jan 2021 23:30:02 +0000

In a pair of announcements, Oxford Instruments NanoScience has disclosed two new customers for its Proteox dilution refrigerator in the UK. The first is with Oxford Quantum Circuit (OQC) which is using the fridge for its superconducting quantum computer based upon OQC's 3D Coaxmon qubits. OQC recently opened up its own quantum lab and plans [...]

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IonQ Partners with South Korea’s Quantum Information Research Support Center

dougfinke1 — Fri, 22 Jan 2021 21:47:53 +0000

The Quantum Information Research Support Center or Q-Center was established in August 2020 by the South Korean government and located at Sungkyunkwan University (SKKU) in Seoul. As part of the three year partnership, IonQ's ion trap computers will be made available to Korean researchers and students to learn, develop, and deploy quantum applications. For more information [...]

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Sufficiently amusing that I had no choice

Scott — Fri, 22 Jan 2021 04:09:45 +0000

BREAKING: President Biden signs executive order banning people from saying “Quantum computers solve problems by just trying all possible solutions in parallel” pic.twitter.com/zeAZvmKA1T
— Olivia Lanes (@Liv_Lanes) January 21, 2021

India’s Ministry of Electronics and Information Technology (MeitY) Partners with AWS To Establish a Quantum Computing Application

dougfinke1 — Thu, 21 Jan 2021 23:31:10 +0000

The MeitY Quantum Computing Applications Lab will provide quantum computing as a service to government ministries and departments, researchers, scientists, academia, and developers, to enable advances in areas such as manufacturing, healthcare, agriculture, and aerospace engineering. In addition to providing access to the Amazon Braket quantum computing service, AWS will provide technical and programmatic support [...]

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India’s Ministry of Electronics and Information Technology (MeitY) Partners with AWS To Establish a Quantum Computing Application Lab

dougfinke1 — Thu, 21 Jan 2021 23:31:10 +0000

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France Plans to Invest 1.8 Billion Euros ($2.19B USD) in Quantum Technologies

dougfinke1 — Thu, 21 Jan 2021 20:28:50 +0000

In a plan presented today by French President Emmanuel Macron, this investment would cover five years of research and development and come from three sources. The French government would increase its annual quantum funding level from €60M to about €200M to bring their share for the period to €1050M, €200M would come from the European [...]

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Researchers improve data readout by using 'quantum entanglement'

Thu, 21 Jan 2021 18:20:30 +0000

Researchers say they have been able to greatly improve the readout of data from digital memories - thanks to a phenomenon known as 'quantum entanglement'.

Innovations through hair-thin optical fibers

Thu, 21 Jan 2021 18:19:59 +0000

Scientists have built hair-thin optical fiber filters in a very simple way. They are not only extremely compact and stable, but also color-tunable. This means they can be used in quantum technology and as sensors for temperature or for detecting atmospheric gases.

Seminal quantum error correction paper included in Physical Review A Milestones List

12011 — Thu, 21 Jan 2021 00:00:00 +0000

Thursday, January 21, 2021

A research paper published in 2012 by Matteo Mariantoni, faculty member at the Institute for Quantum Computing and in the University of Waterloo Department of Physics and Astronomy, appeared on the Physical Review A 50^th Annive

A day to celebrate

Scott — Wed, 20 Jan 2021 19:00:59 +0000

The reason I’m celebrating is presumably obvious to all: today is my daughter Lily’s 8^th birthday! (She had a tiny Star Wars-themed party, dressed in her Rey costume.)

A second reason I’m celebrating yesterday: I began teaching (via Zoom, of course) the latest iteration of my graduate course on Quantum Complexity Theory!

A third reason: I’m now scheduled to get my first covid vaccine shot on Monday! (Texas is working through its “Phase 1b,” which includes both the over-65 and those with underlying conditions—in my case, mild type-2 diabetes.) I’d encourage everyone to do as I did: don’t lie to jump the line, but don’t sacrifice your place either. Just follow the stated rules and get vaccinated the first microsecond you can, and urge all your friends and loved ones to do the same. A crush of demand is actually good if it encourages the providers to expand their hours (they’re taking off weekends! they took off MLK Day!) and not to waste a single dose.

Anyway, people can use this thread to talk about whatever they like, but one thing that would interest me especially is readers’ experiences with vaccination: if you’ve gotten one by now, how hard did you have to look for an appointment, how orderly or chaotic was the process where you live, and what advice can you offer?

Incidentally, to the several commenters on this blog who expressed absolute certainty (as recently as yesterday) that Trump would reverse the election result and be inaugurated instead of Biden, and who confidently accused the rest of us of living in a manufactured media bubble that prevented them from seeing that: I respect that, whatever else is said about you, no one can ever again accuse you of being fair-weather friends!

Congratulations to the new President! There are difficult months ahead, but today the arc of the universe bent slightly toward sanity and goodness.

Qureca Introduces an Online “Quantum for Everyone” Course

dougfinke1 — Wed, 20 Jan 2021 00:46:04 +0000

Qureca's new course is specifically targeted for non-technical business professionals who want to better understand quantum technology so they can build a quantum strategy and find opportunities where it might be applied in their own organization. The course consists of four online lessons which the learner can go through at their own pace. These include: [...]

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Light-controlled Higgs modes found in superconductors; potential sensor, computing uses

Wed, 20 Jan 2021 00:43:55 +0000

Researchers have discovered a short-lived form of the famous Higgs boson -- subject of a groundbreaking search at the Large Hadron Collider -- within an iron-based superconductor. This Higgs mode can be accessed and controlled by laser light flashing on the superconductor at trillions of pulses per second.

One-dimensional quantum nanowires fertile ground for Majorana zero modes

Tue, 19 Jan 2021 15:28:52 +0000

One-dimensional quantum 'nanowires' - which have length, but no width or height - provide a unique environment for the formation and detection of a quasiparticle known as a Majorana zero mode, which are their own antimatter particle. A new advance in detection of these exotic quasiparticles has potential applications in fault-resistant topological quantum computers, and topological superconductivity.

Transforming quantum computing’s promise into practice

Daniel Ackerman | MIT News Office — Tue, 19 Jan 2021 05:00:00 +0000

It was music that sparked William Oliver’s lifelong passion for computers.

Growing up in the Finger Lakes region of New York, he was an avid keyboard player. “But I got into music school on voice,” says Oliver, “because it was a little bit easier.”

But once in school, first at State University of New York at Fredonia then the University of Rochester, he hardly shied away from a challenge. “I was studying sound recording technology, which led me to digital signal processing,” explains Oliver. “And that led me to computers.” Twenty-five years later, he’s still stuck on them.

Oliver, a recently tenured associate professor in MIT’s Department of Electrical Engineering and Computer Science, is building a new class of computer — the quantum computer — with the potential to radically improve how we process information and simulate complex systems. Quantum computing is still in its early days, and Oliver aims to help usher the field out of the laboratory and into the real world. “Our mission is to build the fundamental technologies that are necessary to scale up quantum computing,” he says.

Coast to coast and back again

Oliver’s first stop at MIT was as a master’s student in the Media Lab with adviser Tod Machover. Their interactive Brain Opera project paired Oliver’s love for both music and computing. Oliver orchestrated users’ voices with a computer-generated “angelic arpeggiation of strings and a chorus.” The project was installed at the Haus der Musik museum in Vienna. “It was a fantastic master’s project. I really loved it,” says Oliver. “But the question was ‘okay, what do I do next?’”

Eager for a new challenge, Oliver chose to explore more fundamental research. “I found quantum mechanics to be really puzzling and interesting,” says Oliver. So he traveled to Stanford University to earn a PhD studying quantum optics using free electrons. “I feel very fortunate that I could do those experiments, which have almost no practical application, but that allowed me to think really deeply about quantum mechanics,” he says.

Oliver’s timing was fortunate too. He was delving into quantum mechanics just as the field of quantum computing was emerging. A classical computer, like the one you’re using to read this story, stores information in binary bits, each of which holds a value of 0 or 1. In contrast, a quantum computer stores information in qubits, each of which can hold a 0, 1, or any simultaneous combination of 0 and 1, thanks to a quantum mechanical phenomenon called superposition. That means quantum computers can process information far faster than classical computers, in some cases completing tasks in minutes where a classical computer would take millennia — at least in theory. When Oliver was completing his PhD, quantum computing was a field in its infancy, more idea than reality. But Oliver grasped the potential of quantum computing, so he returned to MIT to help it grow.

The qubit quandary

Quantum computers are frustratingly inconsistent. That’s in part because those qubit superposition states are fragile. In a process called decoherence, qubits can err and lose their quantum information from the slightest disturbance or material defect. In 2003, Oliver took a staff position at MIT’s Lincoln Laboratory to help solve problems like decoherence. His goal, with colleagues Terry Orlando, Leonya Levitov, and Seth Lloyd, was to engineer reliable quantum computing systems that can be scaled up for practical use. “Quantum computing is transitioning from scientific curiosity to technical reality,” says Oliver. “We know that it works at small scale. And we’re now trying to increase the size of the systems so we can do problems that are actually meaningful.”

Even background levels of radiation can trigger decoherence in mere milliseconds. In a recent Nature paper, Oliver and his colleagues, including professor of physics Joe Formaggio, described this problem and proposed ways to shelter qubits from damaging radiation, like shielding them with lead.

He is quick to emphasize the role of collaboration in solving these complex challenges. “Engineering these quantum systems into useful, larger scale machines is going to require almost every department at the Institute,” says Oliver. In his own research, he builds qubits from electrical circuits in aluminum that are supercooled to just a smidge warmer than absolute zero. At that temperature, the system loses electrical resistance and can be used as an anharmonic oscillator that stores quantum information. Engineering such an intricate system to reliably process information means “we need to bring in a lot of people with their own talents,” says Oliver.

“For example, materials scientists will have a lot to say about the materials and the defects on the surfaces,” he adds. “Electrical engineers will have something to say about how to fabricate and control the qubits. Computer scientists and applied mathematicians will have something to say about the algorithms. Chemists and biologists know the hard problems to solve. And so on.” When he first joined Lincoln Laboratory, Oliver says just two Lincoln staff were focused on quantum technologies. That number now exceeds 100.

In 2015, Oliver founded the Engineering Quantum Systems (EQuS) group to focus specifically on superconducting qubit technology. He is also a Lincoln Laboratory Fellow, director of MIT’s Center for Quantum Engineering, and associate director of the Research Laboratory of Electronics.

A quantum future

Oliver envisions a steadily growing role for quantum computing. Already, Google has demonstrated that for a particular task, a 53-qubit quantum computer can far outpace even the world’s largest supercomputer, which features quadrillions of transistors. “That was like the flight at Kitty Hawk,” says Oliver. “It got off the ground.”

In the near-term, Oliver thinks quantum and classical computers could work as partners. The classical machine would churn through an algorithm, dispatching specific calculations for the quantum computer to run before its qubits decohere. In the longer term, Oliver says that error-correcting codes could enable quantum computers to function indefinitely, even as some individual components remain faulty. “And that’s when quantum computers will basically be universal,” says Oliver. “They’ll be able to run any quantum algorithm at large scale.” That could enable vastly improved simulations of complex systems in fields like molecular biology, quantum chemistry, and climatology.

Oliver will continue to push quantum computing toward that reality. “There are real accomplishments that have been happening,” he says. “At the same time, on the theoretical side, there are real problems we could solve if we just had a quantum computer big enough.” While focused on his mission to scale up quantum computing, Oliver hasn’t lost his passion for music. Although, he says he rarely sings these days: “Only in the shower.”

Taking qubits to the next level

12011 — Mon, 18 Jan 2021 00:00:00 +0000

Monday, January 18, 2021

Researchers have implemented a gate used in important quantum algorithms in one step on a three-level quantum system—a qutrit—for the first time.

Bavarian Government Planning a €300 Million ($362M USD) Investment to Establish a Munich Quantum Valley

dougfinke1 — Sun, 17 Jan 2021 01:53:15 +0000

The German Free State of Bavaria will work with the Bavarian Academy of Sciences and Humanities, the Fraunhofer-Gesellschaft, the Ludwig Maximilian University of Munich, the Max-Planck-Gesellschaft and the Technical University of Munich to perform research, development, and education and training in quantum science and technology. Of the €300 million, they plan on spending €120 million ($145M USD) [...]

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New state of matter in one-dimensional quantum gas

Thu, 14 Jan 2021 21:39:13 +0000

By adding some magnetic flair to an exotic quantum experiment, physicists produced an ultra-stable one-dimensional quantum gas with never-before-seen 'scar' states - a feature that could someday be useful for securing quantum information.

New way to control electrical charge in 2D materials: Put a flake on it

Thu, 14 Jan 2021 18:01:21 +0000

Gaining control of the flow of electrical current through atomically thin materials is important to potential future applications in photovoltaics or computing. Physicists have discovered one way to locally add electrical charge to a graphene device.

Pivotal discovery in quantum and classical information processing

Wed, 13 Jan 2021 19:44:20 +0000

Researchers have achieved, for the first time, electronically adjustable interactions between microwaves and a phenomenon in certain magnetic materials called spin waves. This could have application in quantum and classical information processing.

Electrically switchable qubit can tune between storage and fast calculation modes

Mon, 11 Jan 2021 16:22:16 +0000

To perform calculations, quantum computers need qubits to act as elementary building blocks that process and store information. Now, physicists have produced a new type of qubit that can be switched from a stable idle mode to a fast calculation mode. The concept would also allow a large number of qubits to be combined into a powerful quantum computer.

Quantum revolution challenges the world will face

leah — Fri, 08 Jan 2021 21:46:48 +0000

From Interesting Engineering, Jan. 5, 2021: A recent breakthroughs in transmitting, storing, and manipulating quantum information have convinced some physicists that a simple proof of principle for a quantum network is imminent. In 2017, a number of institutions partnered with Fermilab to begin constructing a quantum network hosted at Fermilab.

Entangling electrons with heat

Fri, 08 Jan 2021 13:41:06 +0000

Quantum entanglement is key for next-generation computing and communications technology, researchers can now produce it using temperature differences.

To all Trumpists who comment on this blog

Scott — Wed, 06 Jan 2021 21:01:45 +0000

The violent insurrection now unfolding in Washington DC is precisely the thing you called me nuts, accused me of “Trump Derangement Syndrome,” for warning about since 2016. Crazy me, huh, always seeing brownshirts around the corner? And you called the other side violent anarchists? This is all your doing. So own it. Wallow in it. May you live the rest of your lives in shame. May you never show your faces again.

Physicists observe competition between magnetic orders

Wed, 06 Jan 2021 18:30:50 +0000

Two-dimensional materials, consisting of a single layer of atoms, have been booming in research for years. They possess novel properties that can only be explained with the help of the laws of quantum mechanics. Researchers have now used ultracold atoms to gain new insights into previously unknown quantum phenomena. They found out that the magnetic orders between two coupled thin films of atoms compete with each other.

A bit too much: Reducing the bit width of Ising models for quantum annealing

Wed, 06 Jan 2021 14:53:18 +0000

Quantum annealers are devices that physically implement a quantum system called the 'Ising model' to solve combinatorial optimization problems. However, the coefficients of the Ising model often require a large bit width, making it difficult to implement physically. Now, scientists demonstrate a method to reduce the bit width of any Ising model, increasing the applicability and versatility of quantum annealers in many fields, including cryptography, logistics, and artificial intelligence.

Breaking through the resolution barrier with quantum-limited precision

Tue, 05 Jan 2021 15:48:28 +0000

Researchers have developed a new method of distance measurement for systems such as GPS, which achieves more precise results than ever before. Using quantum physics, the team has successfully overcome the so-called resolution limit.

The unhackable computers that could revolutionize the future

leah — Mon, 04 Jan 2021 20:54:44 +0000

From CNN, Dec. 29, 2020: Researchers are trying to harness the counterintuitive behavior of quantum mechanics to build quantum computers, leading eventually to a quantum internet. The effort isn't just an abstract goal of academics; it has been identified by the U.S. government as an important national initiative. In this opinion piece, Fermilab scientist Don Lincoln discusses the recent quantum teleportation milestone at Fermilab and the quantum internet.

A high order for a low dimension

Mon, 04 Jan 2021 16:41:19 +0000

Spintronics refers to a suite of physical systems which may one day replace many electronic systems. To realize this generational leap, material components that confine electrons in one dimension are highly sought after. For the first time, researchers created such a material in the form of a special bismuth-based crystal known as a high-order topological insulator.

Questing for a quantum solution

18348 — Mon, 04 Jan 2021 00:00:00 +0000

Monday, January 4, 2021

In his most recent collaboration with IBM, IQC and University of Waterloo Combinatorics and Optimization faculty member David Gosset has developed classical algorithms to simulate certain restricted types of quantum computation.

La quête d’une solution quantique

12011 — Mon, 04 Jan 2021 00:00:00 +0000

Monday, January 4, 2021

In English

Dans ses travaux les plus récents menés en collaboration avec IBM, David Gosset, professeur à l’IQC ainsi qu’au Département de combinatoire et d’optimisation, a développé des algorithmes classiques pour simuler certains types restreints de calcul quantique.

Distribute the vaccines NOW!

Scott — Sat, 02 Jan 2021 09:36:18 +0000

My last post about covid vaccines felt like shouting uselessly into the void … at least until Patrick Collison, the cofounder of Stripe and a wonderful friend, massively signal-boosted the post by tweeting it. This business is of such life-and-death urgency right now, and a shift in attitude or a hardening of resolve by just a few people reading could have such an outsized effect, that with apologies to anyone wanting me to return to my math/CS/physics lane, I feel like a second post on the same topic is called for.

Here’s my main point for today (as you might have noticed, I’ve changed the tagline of this entire blog accordingly):

Reasonable people can disagree about whether vaccination could have, or should have, started much earlier. But now that we in the US have painstakingly approved two vaccines, we should all agree about the urgent need to get millions of doses into people’s arms before they spoil! Sure, better the elderly than the young, better essential than inessential workers—but much more importantly, better today than tomorrow, and better anyone than no one!

Israel, which didn’t do especially well in earlier stages of the pandemic, is now putting the rest of the planet to shame with vaccinations. What Dana and I hear from our friends and relatives there confirms what you can read here, here, and elsewhere. Rabin Square in Tel Aviv is now a huge vaccination field site. Vaccinations are now proceeding 24/7, even on Shabbat—something the ultra-Orthodox rabbis are grudgingly tolerating under the doctrine of “pikuach nefesh” (i.e., saving a life overrides almost every other religious obligation). Israelis are receiving texts at all hours telling them when it’s their turn and where to go. Apparently, after the nurses are finished with everyone who had appointments, rather than waste whatever already-thawed supply is left, they simply go into the street and offer the extra doses to anyone passing by.

Contrast that with the historic fiasco—yes, another historic fiasco—now unfolding in the US. The Trump administration had pledged to administer 20 million vaccines (well, Trump originally said 100 million) by the end of 2020. Instead, fewer than three million were administered, with the already-glacial pace slowing even further over the holidays. Unbelievably, millions of doses are on track to spoil this month, before they can be administered. The bottleneck is now not manufacturing, it’s not supply, it’s just pure bureaucratic dysfunction and chaos, lack of funding and staff, and a stone-faced unwillingness by governors to deviate from harebrained “plans” and “guidelines” even with their populations’ survival at stake.

Famously, the CDC urged that essential workers get vaccinated before the elderly, since even though their own modeling predicted that many more people from all ethnic groups would die that way, at least the deaths would be more equitably distributed. While there are some good arguments to prioritize essential workers, an outcry then led to the CDC partially backtracking, and to many states just making up their own guidelines. But we’re now, for real, headed for a scenario where none of these moral-philosophy debates turn out to matter, since the vaccines will simply spoil in freezers (!!!) while the medical system struggles to comply with the Byzantine rules about who gets them first.

While I’d obviously never advocate such a thing, one wonders whether there’s an idealistic medical worker, somewhere in the US, who’s willing to risk jail for vaccinating people without approval, using supply that would otherwise be wasted. If anything could galvanize this sad and declining nation to move faster, maybe it’s that.

In my last post, I invited people to explain to me where I went wrong in my naïve, simplistic, doofus belief that, were our civilization still capable of “WWII” levels of competence, flexibility, and calculated risk-tolerance, most of the world could have already been vaccinated by now. In the rest of this post, I’d like to list the eight most important counterarguments to that position that commenters offered (at least, those that I hadn’t already anticipated in the post itself), together with my brief responses to them.

Faster approval wouldn’t have helped, since the limiting factor was just the time needed to ramp up the supply. As the first part of this post discussed, ironically supply is not now the limiting factor, and approval even a month or two earlier could’ve provided precious time to iron out the massive problems in distribution. More broadly, though, what’s becoming obvious is that we needed faster everything: testing, approval, manufacturing, and distribution.
The real risk, with vaccines, is long-term side effects, ones that might manifest only after years. What I don’t get is, if people genuinely believe this, then why are they OK with having approved the vaccines last month? Why shouldn’t we have waited until 2024, or maybe 2040? By that point, those of us who were still alive could take the covid vaccine with real confidence, at least that the dreaded side effects would be unlikely to manifest before 2060.
Much like with Amdahl’s Law, there are limits to how much more money could’ve sped up vaccine manufacturing. My problem is that, while this is undoubtedly true, I see no indication that we were anywhere close to those limits—or indeed, that the paltry ~$9 billion the US spent on covid vaccines was the output of any rational cost/benefit calculation. It’s like: suppose an enemy army had invaded the US mainland, slaughtered 330,000 people, and shut down much of the economy. Can you imagine Congress responding by giving the Pentagon a 1.3% budget increase to fight back, reasoning that any more would run up against Amdahl’s Law? That’s how much $9 billion is.
The old, inactivated-virus vaccines often took years to develop, so spending years to test them as well made a lot more sense. This is undoubtedly true, but is not a counterargument. It’s time to rethink the whole vaccine approval process for the era of programmable mRNA, which is also the era of pandemics that can spread around the world in months.
Human challenge trials wouldn’t have provided much information, because you can’t do challenge trials with old or sick people, and because covid spread so widely that normal Phase III trials were perfectly informative. Actually, 1DaySooner had plenty of elderly volunteers and volunteers with preexisting conditions. It bothers me how the impossibility of using those volunteers is treated like a law of physics, rather than what it is: another non-obvious moral tradeoff. Also, compared to Phase III trials, it looks like challenge trials would’ve bought us at least a couple months and maybe a half-million lives.
Doctors can’t think like utilitarians—e.g., risking hundreds of lives in challenge trials in order to save millions of lives with a vaccine—because it’s a slippery slope from there to cutting up one person in order to save ten with their organs. Well, I think the informed consent of the challenge trial participants is a pretty important factor here! As is their >99% chance of survival. Look, anyone who works in public health makes utilitarian tradeoffs; the question is whether they’re good or bad ones. As someone who lost most of his extended family in the Holocaust, my rule of thumb is that, if you’re worrying every second about whether you might become Dr. Mengele, that’s a pretty good sign that you won’t become Dr. Mengele.
If a hastily-approved vaccine turned out to be ineffective or dangerous, it could diminish the public’s trust in all future vaccines. Yes, of course there’s such a tradeoff, but I want you to notice the immense irony: this argument effectively says we can condemn millions to die right now, out of concern for hypothetical other millions in the future. And yet some of the people making this argument will then turn around and call me a callous utilitarian!
I’m suffering from hindsight bias: it might be clear now that vaccine approval and distribution should’ve happened a lot faster, but experts had no way of knowing that in the spring. Here’s my post from May 1, entitled “Vaccine challenge trials NOW!” I was encouraged by the many others who said similar things still earlier. Was it just a lucky gamble? Had we been allowed to get vaccinated then, at least we could’ve put our bloodstreams where our mouths were, and profited from the gamble! More seriously, I sympathize with the decision-makers who’d be on the hook had an early vaccine rollout proved disastrous. But if we don’t learn a lesson from this, and ready ourselves for the next pandemic with an mRNA platform that can be customized, tested, and injected into people’s arms within at most 2-3 months, we’ll really have no excuse.

My vaccine crackpottery: a confession

Scott — Thu, 31 Dec 2020 09:16:32 +0000

I hope everyone is enjoying a New Years’ as festive as the circumstances allow!

I’ve heard from a bunch of you awaiting my next post on the continuum hypothesis, and it’s a-comin’, but I confess the new, faster-spreading covid variant is giving me the same sinking feeling that Covid 1.0 gave me in late February, making it really hard to think about the eternal. (For perspectives on Covid 2.0 from individuals who acquitted themselves well with their early warnings about Covid 1.0, see for example this by Jacob Falkovich, or this by Zvi Mowshowitz.)

So on that note: do you hold any opinions, on factual matters of practical importance, that most everyone around you sharply disagrees with? Opinions that those who you respect consider ignorant, naive, imprudent, and well outside your sphere of expertise? Opinions that, nevertheless, you simply continue to hold, because you’ve learned that, unless and until someone shows you the light, you can no more will yourself to change what you think about the matter than change your blood type?

I try to have as few such opinions as possible. Having run Shtetl-Optimized for fifteen years, I’m acutely aware of the success rate of those autodidacts and amateurs who think they’ve solved P versus NP or quantum gravity or whatever. It’s basically zero out of hundreds—and why wouldn’t it be?

And yet there’s one issue where I feel myself in the unhappy epistemic situation of those amateurs, spamming the professors in all caps. So, OK, here it is:

I think that, in a well-run civilization, the first covid vaccines would’ve been tested and approved by around March or April 2020, while mass-manufacturing simultaneously ramped up with trillions of dollars’ investment. I think almost everyone on earth could have, and should have, already been vaccinated by now. I think a faster, “WWII-style” approach would’ve saved millions of lives, prevented economic destruction, and carried negligible risks compared to its benefits. I think this will be clear to future generations, who’ll write PhD theses exploring how it was possible that we invented multiple effective covid vaccines in mere days or weeks, but then simply sat on those vaccines for a year, ticking off boxes called “Phase I,” “Phase II,” etc. while civilization hung in the balance.

I’ve said similar things, on this blog and elsewhere, since the beginning of the pandemic, but part of me kept expecting events to teach me why I was wrong. Instead events—including the staggering cost of delay, the spectacular failures of institutional authorities to adapt to scientific realities of covid, and the long-awaited finding that all the major vaccines safely work (some better than others), just like the experts predicted back in February—all this only made me more confident of my original, stupid, naïve position.

I’m saying all this—clearly enough that no one will misunderstand—but I’m also scared to say it. I’m scared because it sounds too much like colossal ingratitude, like Monday-morning quarterbacking of one of the great heroic achievements of our time by someone who played no part in it.

Let’s be clear: the ~11 months that it took to get from sequencing the novel coronavirus, to approving and mass-manufacturing, is a world record, beating the previous record of 4 years. Nobel Prizes and billions of dollars are the least that those who made this possible deserve. Eternal praise is especially due to those like Katalin Karikó, who risked their careers in the decades before covid to do the basic research into mRNA delivery that made the development of these mRNA vaccines so blindingly fast.

Furthermore, I could easily believe that there’s no one agent—neither Pfizer nor BioNTech nor Moderna, neither the CDC nor FDA nor other health or regulatory agencies, neither Bill Gates nor Moncef Slaoui—who could’ve unilaterally sped things up very much. If one of them tried, they would’ve simply been ostracized by the other parts of the system, and they probably all understood this. It might have taken a whole different civilization, with different attitudes about utility and risk.

And yet the fact remains that, historic though it was, a one-to-two-year turnaround time wasn’t nearly good enough. Especially once we factor in the faster-spreading variant, by the time we’ve vaccinated everyone, we’ll already be a large fraction of the way to herd immunity and to the vaccine losing its purpose. For all the advances in civilization, from believing in demonic spirits to understanding mRNA at a machine-code level of detail, covid is running wild much like it would have back in the Middle Ages—partly, yes, because modern transportation helps it spread, but partly because our political and regulatory and public-health tools have lagged so breathtakingly far behind our knowledge of molecular biology.

What could’ve been done faster? For starters, as I said back in March, we could’ve had human challenge trials with willing volunteers, of whom there were tens of thousands. We could’ve started mass-manufacturing six months earlier, with WWII levels of funding. Today, we could give as many people as possible the first doses (which apparently already provide something like ~80% protection) before circling back to give the second doses (which boost the protection as high as ~95%). We could distribute the vaccines that are now sitting in warehouses, spoiling, while people in the distribution chain take off for the holidays—but that’s such low-hanging fruit that it feels unsporting even to mention it.

Let me now respond to three counterarguments that would surely come up in the comments if I didn’t address them.

The Argument from Actual Risk. Every time this subject arises, someone patiently explains to me that, since a vaccine gets administered to billions of healthy people, the standards for its safety and efficacy need to be even higher than they are for ordinary medicines. Of course that’s true, and it strikes me as a good reason not to rush to inject people with a completely untested vaccine! All I ask is that the people who are, or could be, harmed by a faulty vaccine, be weighed on exactly the same moral scale as the people harmed by covid itself. As an example, we know that the Phase III clinical trials were repeatedly halted for days or weeks because of a single participant developing strange symptoms—often a participant who’d received the placebo rather than the actual vaccine! That person matters. Any future vaccine recipient who might develop similar symptoms matters. But the 10,000 people who die of covid every single day we delay, along with the hundreds of millions more impoverished, kept out of school, etc., matter equally. If we threw them all onto the same utilitarian scale, would we be making the same tradeoffs that we are now? I feel like the question answers itself.
The Argument from Perceived Risk. Even with all the testing that’s been done, somewhere between 16% and 40% of Americans (depending on which poll you look at) say that they’ll refuse to get a covid vaccine, often because of anti-vaxx conspiracy theories. How much higher would the percentage be had the vaccines been rushed out in a month or two? And of course, if not enough people get vaccinated, then R₀ romains above 1 and the whole public-health campaign is a failure. In this way of thinking, we need three phases of clinical trials the same way we need everyone to take off their shoes at airport security: it might not prevent a single terrorist, but people will be too scared to get on the planes if we don’t. To me, this (if true) only underscores my broader point, that the year-long delay in getting vaccines out represents a failure of our entire civilization, rather than a failure of any one agent. But also: people’s membership in the pro- or anti-vaxx camps is not static. The percentage saying they’ll get a covid vaccine seems to have already gone up, as a formerly abstract question becomes a stark choice between wallowing in delusions and getting a deadly disease, or accepting reality and not getting it. Even while the Phase III trials were still underway—when the vaccines were already known to be safe, and experts thought it much more likely than not that they’d work—would it have been a disaster to let Pfizer and Moderna sell the vaccines to those who wanted them? With the hope that, just like with the iPhone or any other successful consumer product, satisfied early adopters would inspire the more reticent to get one too?
The Argument from Trump. Now for the most awkward counterargument, which I’m going to address head-on rather than dodge. If the vaccines had been approved faster in the US, it would’ve looked to many like Trump deserved credit for it, and he might well have been reelected. And devastating though covid has been, Trump is plausibly worse! Here’s my response: Trump has the mentality of a toddler, albeit with curiosity swapped out for cruelty and vindictiveness. His and his cronies’ impulsivity, self-centeredness, and incompetence are likely responsible for at least ~200,000 of the 330,000 Americans now dead from covid. But, yes, reversing his previous anti-vaxx stance, Trump did say that he wanted to see a covid vaccine in months, just like I’ve said. Does it make me uncomfortable to have America’s worst president in my “camp”? Only a little, because I have no problem admitting that sometimes toddlers are right and experts are wrong. But the solution, I’d say, is not to put toddlers in charge of the government! As should be obvious by now—indeed, as should’ve been obvious in 2016—that solution has some exceedingly severe downsides. The solution, rather, is to work for a world where experts are unafraid to speak bluntly, so that it never falls to a mental toddler to say what the experts can’t say without jeopardizing their careers.

Anyway, despite everything I’ve written, considerations of Aumann’s Agreement Theorem still lead me to believe there’s an excellent chance that I’m wrong, and the vaccines couldn’t realistically have been rolled out any faster. The trouble is, I don’t understand why. And I don’t understand why compressing this process, from a year or two to at most a month or two, shouldn’t be civilization’s most urgent priority ahead of the next pandemic. So go ahead, explain it to me! I’ll be eternally grateful to whomever makes me retract this post in shame.

Important milestone in the creation of a quantum computer

Mon, 28 Dec 2020 15:18:07 +0000

One of the obstacles for progress in the quest for a working quantum computer has been that the working devices that go into a quantum computer and perform the actual calculations, the qubits, have hitherto been made by universities and in small numbers. But in recent years, a pan-European collaboration has been exploring everyday transistors -- that are present in billions in all our mobile phones -- for their use as qubits.

Perfect transmission through barrier using sound

Wed, 23 Dec 2020 17:57:45 +0000

A research team has for the first time experimentally proved a century old quantum theory that relativistic particles can pass through a barrier with 100% transmission.

Quantum wave in helium dimer filmed for the first time

Wed, 23 Dec 2020 17:57:34 +0000

For the first time, an international team of scientists has succeeded in filming quantum physical effects on a helium dimer as it breaks apart. The film shows the superposition of matter waves from two simultaneous events that occur with different probability: The survival and the disintegration of the helium dimer. This method might in future make it possible to track experimentally the formation and decay of quantum Efimov systems.

The case for moving to a red state

Scott — Tue, 22 Dec 2020 08:05:19 +0000

The US is now a failed democracy, with a president who’s considering declaring martial law to avoid conceding a lost election, and with the majority of his party eager to follow him arbitrarily far into the abyss. Even assuming, as I do, that the immediate putsch will fail, the Republic will not magically return to normal.
The survival of Enlightenment values on Earth now depends, in large part, on the total electoral humiliation and defeat of the forces that enabled Trump—something that the last election failed to deliver.
Alas, ever since it absorbed the Southern racists in the 1960s, the Republican Party has maintained a grip on power wholly out of proportion to its numbers through anti-democratic means. The most durable of these means are built into the Constitution itself: the Electoral College, the overrepresentation of sparsely-populated rural states in the Senate, and the gerrymandering of Congressional districts. Every effort to fix these anachronisms, whether by legislation or Constitutional amendment, has been blocked for generations. It’s fantasy to imagine the beneficiaries of these unjust advantages ever voluntarily giving them up.
Accordingly, the survival of the nation might come down to whether enough Americans, in deep-blue areas like California and New York and Massachusetts, are willing to pick up and move to where their votes actually count.
The pandemic has awoken tens of millions of people to the actual practical feasibility of working from home or in a different time zone from their employer. The culture has finally caught up to the abridgment of distance that the Internet, smartphones, and videoconferencing achieved well over a decade ago.
Still, one doesn’t expect Brooklynites to settle by the thousands on remote mountaintops. And even if they did, there are many remote mountaintops, so the transplants’ power could be diluted to near nothing. Better for the transplants to concentrate themselves in a few Schelling points: ideally, cities where they could both swing the national electoral calculus and actually want to live.
There’s been a spate of recent articles about the possible exodus of tech companies and professionals from the Bay Area, because of whatever combination of sky-high rents, NIMBYism, taxes, mismanagement, wildfires, blackouts, and the pandemic having removed the once-overwhelming reasons to be in the Bay. Oft-mentioned alternatives include Miami, Denver, and of course my own adopted hometown of Austin, TX, where Elon Musk and Oracle just announced they’re moving.
If you were trying to optimize your environment for urban Blue-Tribeyness—indie music, craft beer, ironic tattoos, Bernie Sanders yard signs, etc. etc.—but subject to living in an important red or purple state, where your vote could plausibly contribute to a historic political realignment of the US—then you couldn’t do much better than Austin. Where else is even in the running? Atlanta, Houston, San Antonio, Pittsburgh?
It’s true that Texas is the state of Ken Paxton, the corrupt and unhinged Attorney General who unsuccessfully petitioned the US Supreme Court to overturn Trump’s election loss. But it’s also the state of MD Anderson, often considered the best oncology center on earth, and of Steven Weinberg, possibly the greatest living physicist. It’s where the spike proteins of both the Pfizer and Moderna covid vaccines were developed. It’s where Sheldon Cooper grew up—alright, he’s fictional, but I’ve worked with undergrads at UT Austin who almost could’ve been Sheldon. Like the US as a whole, the state has potential.
Accelerating the mass migration of blue Americans to cities like Austin isn’t only good for the country and the world. The New Yorkers and San Franciscans left behind will thank the migrants for their lower rents!
But won’t climate change make Texas a living hell? Alas, as recent wildfires and hurricanes remind us, there aren’t many places on earth that climate change won’t soon make various shades of hell. At least Austin, like many red locales, is far inland. For the summers, there are lots of swimming pools and lakes.
If Austin gets overrun by Silicon Valley refugees, won’t they recreate whatever dysfunctional conditions caused them to flee Silicon Valley in the first place? Maybe, eventually, but it would take quite a while. One problem at a time!
Is Texas winnable—or is a blue Texas like controlled nuclear fusion, forever a decade or two in the future? Well, Trump’s 6-point margin in Texas this November, 3 points less than his margin in 2016, amounted to 630,000 votes out of 11.3 million cast. Meanwhile, net migration to Texas over the past decade included 356,000 to Austin (growing its population by 20%), 687,000 to Dallas, 603,000 to Houston, 260,000 to San Antonio. Let’s say we want two million more transplants (obviously they won’t all vote, and those who do won’t all vote blue). The question is not whether they’re going to come here but at what rate.
Can the cities of Texas accommodate two million more knowledge workers? Well, traffic will get worse, rents will get higher … but the answer is an unequivocal yes. Land, Texas has.
Do the tech workers who I’d like to relocate even vote Democratic? Given the unremitting scorn that the woke press now heaps on racist, sexist, greedy Silicon Valley techbros, it can be easy to forget this, but the answer to the question is: yes, overwhelmingly, they do. Mountain View, CA, for example, went 83% Biden and only 15% Trump in November.
Even if everything I’ve said is obvious, in order for the Great Red-State Tech-Worker Migration happen at the rate I want, it needs to become common knowledge that it’s happening—not merely known but known to be known, and so forth. Closely related, it needs to become a serious status symbol for any blue-triber to relocate to a contested state. (“You’re moving to Georgia to help save the Republic? I’m so jealous!”)
This has been the real purpose of this post: to make it clear that, if you help settle the wild frontier like my family did, then a tiny bit of the unattainable coolness of a stuttering quantum complexity theory blogger/professor could rub off on you.
Think about it this way. Many of our grandparents gave their lives to save the world from fascism. Would you have done the same in their stead? OK now, what if you didn’t have to lose your life: you only had to live in Austin, Miami, or Houston?
If this post plays a role in any like-minded reader’s decision to move to Austin, then once covid is over, they should tell me to redeem a personal welcome celebration from me and Dana. We’ll throw some extra brisket on the barbie.

2020 IQC Achievement Award winner announced

12011 — Fri, 18 Dec 2020 00:00:00 +0000

Friday, December 18, 2020

The Institute for Quantum Computing’s (IQC) Achievement Award is given to a University of Waterloo graduate student who studies quantum information and has achieved excellence in research. The latest winner, Michal Kononenko, talked with us about his Master’s research, keeping quantum information science relevant, and his advice for students thinking about studying in the field.

Annonce du lauréat du prix d’excellence 2020 de l’IQC

12011 — Fri, 18 Dec 2020 00:00:00 +0000

Friday, December 18, 2020

In English

Le prix d’excellence de l’Institut d’informatique quantique (IQC) est remis à une personne qui fait des études supérieures en informatique quantique à l’Université de Waterloo et qui s’est distinguée par son excellence en recherche. Dernier lauréat en date, Michal Kononenko nous a parlé de ses recherches de maîtrise, de la pertinence de l’informatique quantique et des conseils qu’il donne à ceux qui songent à étudier dans ce domaine.

Scientists create entangled photons 100 times more efficiently than previously possible

Thu, 17 Dec 2020 18:54:11 +0000

Super-fast quantum computers and communication devices could revolutionize countless aspects of our lives -- but first, researchers need a fast, efficient source of the entangled pairs of photons such systems use to transmit and manipulate information. Researchers have done just that, not only creating a chip-based photon source 100 times more efficient that previously possible, but bringing massive quantum device integration within reach.

Researchers have achieved sustained long-distance quantum teleportation

lindseya — Thu, 17 Dec 2020 16:42:20 +0000

From VICE, Dec. 17, 2020: Fermilab and partners have successfully teleported qubits across 22 kilometers of fiber in two testbeds. The breakthrough is a step towards a practical, high-fidelity quantum internet. Fermilab scientist and Quantum Science Program Head Panagiotis Spentzouris is quoted in this article.

Tiny quantum computer solves real optimization problem

Thu, 17 Dec 2020 14:04:04 +0000

Quantum computers have already managed to surpass ordinary computers in solving certain tasks - unfortunately, totally useless ones. The next milestone is to get them to do useful things. Researchers have now shown that they can solve a small part of a real logistics problem with their small, but well-functioning quantum computer.

Information transport in antiferromagnets via pseudospin-magnons

Wed, 16 Dec 2020 18:47:20 +0000

A team of researchers has discovered an exciting method for controlling spin carried by quantized spin wave excitations in antiferromagnetic insulators.

Ultracold atoms reveal a new type of quantum magnetic behavior

Jennifer Chu | MIT News Office — Wed, 16 Dec 2020 16:00:00 +0000

A new study illuminates surprising choreography among spinning atoms. In a paper appearing today in the journal Nature, researchers from MIT and Harvard University reveal how magnetic forces at the quantum, atomic scale affect how atoms orient their spins.

In experiments with ultracold lithium atoms, the researchers observed different ways in which the spins of the atoms evolve. Like tippy ballerinas pirouetting back to upright positions, the spinning atoms return to an equilibrium orientation in a way that depends on the magnetic forces between individual atoms. For example, the atoms can spin into equilibrium in an extremely fast, “ballistic” fashion or in a slower, more diffuse pattern.

The researchers found that these behaviors, which had not been observed until now, could be described mathematically by the Heisenberg model, a set of equations commonly used to predict magnetic behavior. Their results address the fundamental nature of magnetism, revealing a diversity of behavior in one of the simplest magnetic materials.

This improved understanding of magnetism may help engineers design “spintronic” devices, which transmit, process, and store information using the spin of quantum particles rather than the flow of electrons.

“Studying one of the simplest magnetic materials, we have advanced the understanding of magnetism,” says Wolfgang Ketterle, the John D. Arthur professor of physics at MIT and the leader of the MIT team. “When you find new phenomena in one of the simplest models in physics for magnetism, then you have a chance to fully describe and understand it. This is what gets me out of bed in the morning, and gets me excited.”

Ketterle’s co-authors are MIT graduate student and lead author Paul Niklas Jepsen, along with Jesse-Amato Grill, Ivana Dimitrova, both MIT postdocs, Wen Wei Ho, a postdoc at Harvard University and Stanford University, and Eugene Demler, a professor of physics at Harvard. All are researchers in the MIT-Harvard Center for Ultracold Atoms. The MIT team is affiliated with the Institute’s Department of Physics and Research Laboratory of Electronics.

Strings of spins

Quantum spin is considered the microscopic unit of magnetism. At the quantum scale, atoms can spin clockwise or counterclockwise, which gives them an orientation, like a compass needle. In magnetic materials, the spin of many atoms can show a variety of phenomena, including equilibrium states, where atom spins are aligned, and dynamic behavior, where the spins across many atoms resemble a wave-like pattern.

It is this latter pattern which was studied by the researchers. The dynamics of the wavelike spin pattern are very sensitive to the magnetic forces between atoms. The wavy pattern faded away much faster for isotropic magnetic forces than for anisotropic forces. (Isotropic forces don’t depend on how all the spins are oriented in space).

Ketterle’s group aimed to study this phenomenon with an experiment in which they first used established laser-cooling techniques to bring lithium atoms down to about 50 nanokelvin — more than 10 million times colder than interstellar space.

At such ultracold temperatures, atoms are frozen to a near standstill, so that researchers can see in detail any magnetic effects that would otherwise be masked by the thermal motion of the atoms. The researchers then used a system of lasers to trap and arrange multiple strings with 40 atoms each, like beads on a string. In all, they generated a lattice of about 1,000 strings, comprising about 40,000 atoms.

“You can think of the lasers as tweezers that grab the atoms, and if they are warmer they would escape,” Jepsen explains.

They then applied a pattern of radio waves and a pulsed magnetic force to the entire lattice, which induced each atom along the string to tilt its spin into a helical (or wavelike) pattern. The wave-like patterns of these strings together corresponds to a periodic density modulation of the “spin up” atoms that forms a pattern of stripes, which the researchers could image on a detector. They then watched how the stripe patterns disappeared as the individual spins of the atoms approached their equilibrium state.

Ketterle compares the experiment to plucking the string of a guitar. If the researchers were to look at the spins of atoms at equilibrium, this wouldn’t tell them much about the magnetic forces between the atoms, just as a guitar string at rest wouldn’t reveal much about its physical properties. By plucking the string, bringing it out of equilibrium, and seeing how it vibrates and eventually returns to its original state, one can learn something fundamental about the string’s physical properties.

“What we’re doing here is, we’re kind of plucking the string of spins. We’re putting in this helix pattern, and then observing how this pattern behaves as a function of time,” Ketterle says. “This allows us to see the effect of different magnetic forces between the spins.”

Ballistics and ink

In their experiment, the researchers altered the strength of the pulsed magnetic force they applied, to vary the width of the stripes in the atomic spin patterns. They measured how quickly, and in what ways, the patterns faded. Depending on the nature of magnetic forces between atoms, they observed strikingly different behavior in how quantum spins returned to equilibrium.

They discovered a transition between ballistic behavior, where the spins shot quickly back into an equilibrium state, and diffusive behavior, where the spins propagate more erratically, and the overall stripe pattern spread slowly back to equilibrium, like an ink drop slowly dissolving in water.

Some of this behavior has been theoretically predicted, but never observed in detail until now. Some other results were completely unexpected. What’s more, the researchers found their observations fit mathematically with what they calculated with the Heisenberg model for their experimental parameters. They teamed up with theorists at Harvard, who performed state-of-the art calculations of the spin dynamics.

“It was interesting to see that there were properties which were easy to measure, but difficult to calculate, and other properties could be calculated, but not measured,” Ho says.

In addition to advancing the understanding of magnetism at a fundamental level, the team’s results may be used to explore the properties of new materials, as a sort of quantum simulator. Such a platform could work like a special-purpose quantum computer that calculates the behavior of materials, in a way that exceeds the capabilities of today’s most powerful computers .

“With all of the current excitement about the promise of quantum information science to solve practical problems in the future, it is great to see work like this actually coming to fruition today," says John Gillaspy, program officer in the Division of Physics at the National Science Foundation, a funder of the research.

The research was also supported by the Department of Defense and the Gordon and Betty Moore Foundation.

Chinese BosonSampling experiment: the gloves are off

Scott — Wed, 16 Dec 2020 08:16:30 +0000

Two weeks ago, I blogged about the striking claim, by the group headed by Chaoyang Lu and Jianwei Pan at USTC in China, to have achieved quantum supremacy via BosonSampling with 50-70 detected photons. I also did a four-part interview on the subject with Jonathan Tennenbaum at Asia Times, and other interviews elsewhere. None of that stopped some people, who I guess didn’t google, from writing to tell me how disappointed they were by my silence!

The reality, though, is that a lot has happened since the original announcement, so it’s way past time for an update.

I. The Quest to Spoof

Most importantly, other groups almost immediately went to work trying to refute the quantum supremacy claim, by finding some efficient classical algorithm to spoof the reported results. It’s important to understand that this is exactly how the process is supposed to work: as I’ve often stressed, a quantum supremacy claim is credible only if it’s open to the community to refute and if no one can. It’s also important to understand that, for reasons we’ll go into, there’s a decent chance that people will succeed in simulating the new experiment classically, although they haven’t yet. All parties to the discussion agree that the new experiment is, far and away, the closest any BosonSampling experiment has ever gotten to the quantum supremacy regime; the hard part is to figure out if it’s already there.

Part of me feels guilty that, as one of reviewers on the Science paper—albeit, one stressed and harried by kids and covid—it’s now clear that I didn’t exercise the amount of diligence that I could have, in searching for ways to kill the new supremacy claim. But another part of me feels that, with quantum supremacy claims, much like with proposals for new cryptographic codes, vetting can’t be the responsibility of one or two reviewers. Instead, provided the claim is serious—as this one obviously is—the only thing to do is to get the paper out, so that the entire community can then work to knock it down. Communication between authors and skeptics is also a hell of a lot faster when it doesn’t need to go through a journal’s editorial system.

Not surprisingly, one skeptic of the new quantum supremacy claim is Gil Kalai, who (despite Google’s result last year, which Gil still believes must be in error) rejects the entire possibility of quantum supremacy on quasi-metaphysical grounds. But other skeptics are current and former members of the Google team, including Sergio Boixo and John Martinis! And—pause to enjoy the irony—Gil has effectively teamed up with the Google folks on questioning the new claim. Another central figure in the vetting effort—one from whom I’ve learned much of what I know about the relevant issues over the last week—is Dutch quantum optics professor and frequent Shtetl-Optimized commenter Jelmer Renema.

Without further ado, why might the new experiment, impressive though it was, be efficiently simulable classically? A central reason for concern is photon loss: as Chaoyang Lu has now explicitly confirmed (it was implicit in the paper), up to ~70% of the photons get lost on their way through the beamsplitter network, leaving only ~30% to be detected. At least with “Fock state” BosonSampling—i.e., the original kind, the kind with single-photon inputs that Alex Arkhipov and I proposed in 2011—it seems likely to me that such a loss rate would be fatal for quantum supremacy; see for example this 2019 paper by Renema, Shchesnovich, and Garcia-Patron.

Incidentally, if anything’s become clear over the last two weeks, it’s that I, the co-inventor of BosonSampling, am no longer any sort of expert on the subject’s literature!

Anyway, one source of uncertainty regarding the photon loss issue is that, as I said in my last post, the USTC experiment implemented a 2016 variant of BosonSampling called Gaussian BosonSampling (GBS)—and Jelmer tells me that the computational complexity of GBS in the presence of losses hasn’t yet been analyzed in the relevant regime, though there’s been work aiming in that direction. A second source of uncertainty is simply that the classical simulations work in a certain limit—namely, fixing the rate of noise and then letting the numbers of photons and modes go to infinity—but any real experiment has a fixed number of photons and modes (in USTC’s case, they’re ~50 and ~100 respectively). It wouldn’t do to reject USTC’s claim via a theoretical asymptotic argument that would equally well apply to any non-error-corrected quantum supremacy demonstration!

OK, but if an efficient classical simulation of lossy GBS experiments exists, then what is it? How does it work? It turns out that we have a plausible candidate for the answer to that, originating with a 2014 paper by Gil Kalai and Guy Kindler. Given a beamsplitter network, Kalai and Kindler considered an infinite hierarchy of better and better approximations to the BosonSampling distribution for that network. Roughly speaking, at the first level (k=1), one pretends that the photons are just classical distinguishable particles. At the second level (k=2), one correctly models quantum interference involving pairs of photons, but none of the higher-order interference. At the third level (k=3), one correctly models three-photon interference, and so on until k=n (where n is the total number of photons), when one has reproduced the original BosonSampling distribution. At least when k is small, the time needed to spoof outputs at the k^th level of the hierarchy should grow like n^k. As theoretical computer scientists, Kalai and Kindler didn’t care whether their hierarchy produced any physically realistic kind of noise, but later work, by Shchesnovich, Renema, and others, showed that (as it happens) it does.

In its original paper, the USTC team ruled out the possibility that the first, k=1 level of this hierarchy could explain its experimental results. More recently, in response to inquiries by Sergio, Gil, Jelmer, and others, Chaoyang tells me they’ve ruled out the possibility that the k=2 level can explain their results either. We’re now eagerly awaiting the answer for larger values of k.

Let me add that I owe Gil Kalai the following public mea culpa. While his objections to QC have often struck me as unmotivated and weird, in the case at hand, Gil’s 2014 work with Kindler is clearly helping drive the scientific discussion forward. In other words, at least with BosonSampling, it turns out that Gil put his finger precisely on a key issue. He did exactly what every QC skeptic should do, and what I’ve always implored the skeptics to do.

II. BosonSampling vs. Random Circuit Sampling: A Tale of HOG and CHOG and LXEB

There’s a broader question: why should skeptics of a BosonSampling experiment even have to think about messy details like the rate of photon losses? Why shouldn’t that be solely the experimenters’ job?

To understand what I mean, consider the situation with Random Circuit Sampling, the task Google demonstrated last year with 53 qubits. There, the Google team simply collected the output samples and fed them into a benchmark that they called “Linear Cross-Entropy” (LXEB), closely related to what Lijie Chen and I called “Heavy Output Generation” (HOG) in a 2017 paper. With suitable normalization, an ideal quantum computer would achieve an LXEB score of 2, while classical random guessing would achieve an LXEB score of 1. Crucially, according to a 2019 result by me and Sam Gunn, under a plausible (albeit strong) complexity assumption, no subexponential-time classical spoofing algorithm should be able to achieve an LXEB score that’s even slightly higher than 1. In its experiment, Google reported an LXEB score of about 1.002, with a confidence interval much smaller than 0.002. Hence: quantum supremacy (subject to our computational assumption), with no further need to know anything about the sources of noise in Google’s chip! (More explicitly, Boixo, Smelyansky, and Neven did a calculation in 2017 to show that the Kalai-Kindler type of spoofing strategy definitely isn’t going to work against RCS and Linear XEB, with no computational assumption needed.)

So then why couldn’t the USTC team do something analogous with BosonSampling? Well, they tried to. They defined a measure that they called “HOG,” although it’s different from my and Lijie Chen’s HOG, more similar to a cross-entropy. Following Jelmer, let me call their measure CHOG, where the C could stand for Chinese, Chaoyang’s, or Changed. They calculated the CHOG for their experimental samples, and showed that it exceeds the CHOG that you’d get from the k=1 and k=2 levels of the Kalai-Kindler hierarchy, as well as from various other spoofing strategies, thereby ruling those out as classical explanations for their results.

The trouble is this: unlike with Random Circuit Sampling and LXEB, with BosonSampling and CHOG, we know that there are fast classical algorithms that achieve better scores than the trivial algorithm, the algorithm that just picks samples at random. That follows from Kalai and Kindler’s work, and it even more simply follows from a 2013 paper by me and Arkhipov, entitled “BosonSampling Is Far From Uniform.” Worse yet, with BosonSampling, we currently have no analogue of my 2019 result with Sam Gunn: that is, a result that would tell us (under suitable complexity assumptions) the highest possible CHOG score that we expect any efficient classical algorithm to be able to get. And since we don’t know exactly where that ceiling is, we can’t tell the experimentalists exactly what target they need to surpass in order to claim quantum supremacy. Absent such definitive guidance from us, the experimentalists are left playing whac-a-mole against this possible classical spoofing strategy, and that one, and that one.

This is an issue that I and others were aware of for years, although the new experiment has certainly underscored it. Had I understood just how serious the USTC group was about scaling up BosonSampling, and fast, I might’ve given the issue some more attention!

III. Fock vs. Gaussian BosonSampling

Above, I mentioned another complication in understanding the USTC experiment: namely, their reliance on Gaussian BosonSampling (GBS) rather than Fock BosonSampling (FBS), sometimes also called Aaronson-Arkhipov BosonSampling (AABS). Since I gave this issue short shrift in my previous post, let me make up for it now.

In FBS, the initial state consists of either 0 or 1 photons in each input mode, like so: |1,…,1,0,…,0⟩. We then pass the photons through our beamsplitter network, and measure the number of photons in each output mode. The result is that the amplitude of each possible output configuration can be expressed as the permanent of some n×n matrix, where n is the total number of photons. It was interest in the permanent, which plays a central role in classical computational complexity, that led me and Arkhipov to study BosonSampling in the first place.

The trouble is, preparing initial states like |1,…,1,0,…,0⟩ turns out to be really hard. No one has yet build a source that reliably outputs one and only one photon at exactly a specified time. This led two experimental groups to propose an idea that, in a 2013 post on this blog, I named Scattershot BosonSampling (SBS). In SBS, you get to use the more readily available “Spontaneous Parametric Down-Conversion” (SPDC) photon sources, which output superpositions over different numbers of photons, of the form $$\sum_{n=0}^{\infty} \alpha_n |n \rangle |n \rangle, $$ where α_n decreases exponentially with n. You then measure the left half of each entangled pair, hope to see exactly one photon, and are guaranteed that if you do, then there’s also exactly one photon in the right half. Crucially, one can show that, if Fock BosonSampling is hard to simulate approximately using a classical computer, then the Scattershot kind must be as well.

OK, so what’s Gaussian BosonSampling? It’s simply the generalization of SBS where, instead of SPDC states, our input can be an arbitrary “Gaussian state”: for those in the know, a state that’s exponential in some quadratic polynomial in the creation operators. If there are m modes, then such a state requires ~m² independent parameters to specify. The quantum optics people have a much easier time creating these Gaussian states than they do creating single-photon Fock states.

While the amplitudes in FBS are given by permanents of matrices (and thus, the probabilities by the absolute squares of permanents), the probabilities in GBS are given by a more complicated matrix function called the Hafnian. Roughly speaking, while the permanent counts the number of perfect matchings in a bipartite graph, the Hafnian counts the number of perfect matchings in an arbitrary graph. The permanent and the Hafnian are both #P-complete. In the USTC paper, they talk about yet another matrix function called the “Torontonian,” which was invented two years ago. I gather that the Torontonian is just the modification of the Hafnian for the situation where you only have “threshold detectors” (which decide whether one or more photons are present in a given mode), rather than “number-resolving detectors” (which count how many photons are present).

If Gaussian BosonSampling includes Scattershot BosonSampling as a special case, and if Scattershot BosonSampling is at least as hard to simulate classically as the original BosonSampling, then you might hope that GBS would also be at least as hard to simulate classically as the original BosonSampling. Alas, this doesn’t follow. Why not? Because for all we know, a random GBS instance might be a lot easier than a random SBS instance. Just because permanents can be expressed using Hafnians, doesn’t mean that a random Hafnian is as hard as a random permanent.

Nevertheless, I think it’s very likely that the sort of analysis Arkhipov and I did back in 2011 could be mirrored in the Gaussian case. I.e., instead of starting with reasonable assumptions about the distribution and hardness of random permanents, and then concluding the classical hardness of approximate BosonSampling, one would start with reasonable assumptions about the distribution and hardness of random Hafnians (or “Torontonians”), and conclude the classical hardness of approximate GBS. But this is theoretical work that remains to be done!

IV. Application to Molecular Vibronic Spectra?

In 2014, Alan Aspuru-Guzik and collaborators put out a paper that made an amazing claim: namely that, contrary to what I and others had said, BosonSampling was not an intrinsically useless model of computation, good only for refuting QC skeptics like Gil Kalai! Instead, they said, a BosonSampling device (specifically, what would later be called a GBS device) could be directly applied to solve a practical problem in quantum chemistry. This is the computation of “molecular vibronic spectra,” also known as “Franck-Condon profiles,” whatever those are.

I never understood nearly enough about chemistry to evaluate this striking proposal, but I was always a bit skeptical of it, for the following reason. Nothing in the proposal seemed to take seriously that BosonSampling is a sampling task! A chemist would typically have some specific numbers that she wants to estimate, of which these “vibronic spectra” seemed to be an example. But while it’s often convenient to estimate physical quantities via Monte Carlo sampling over simulated observations of the physical system you care about, that’s not the only way to estimate physical quantities! And worryingly, in all the other examples we’d seen where BosonSampling could be used to estimate a number, the same number could also be estimated using one of several polynomial-time classical algorithms invented by Leonid Gurvits. So why should vibronic spectra be an exception?

After an email exchange with Alex Arkhipov, Juan Miguel Arrazola, Leonardo Novo, and Raul Garcia-Patron, I believe we finally got to the bottom of it, and the answer is: vibronic spectra are not an exception.

In terms of BosonSampling, the vibronic spectra task is simply to estimate the probability histogram of some weighted sum like $$ w_1 s_1 + \cdots + w_ m s_m, $$ where w₁,…,w_m are fixed real numbers, and (s₁,…,s_m) is a possible outcome of the BosonSampling experiment, s_i representing the number of photons observed in mode i. Alas, while it takes some work, it turns out that Gurvits’s classical algorithms can be adapted to estimate these histograms. Granted, running the actual BosonSampling experiment would provide slightly more detailed information—namely, some exact sampled values of $$ w_1 s_1 + \cdots + w_ m s_m, $$ rather than merely additive approximations to the values—but since we’d still need to sort those sampled values into coarse “bins” in order to compute a histogram, it’s not clear why that additional precision would ever be of chemical interest.

This is a pity, since if the vibronic spectra application had beaten what was doable classically, then it would’ve provided not merely a first practical use for BosonSampling, but also a lovely way to verify that a BosonSampling device was working as intended.

V. Application to Finding Dense Subgraphs?

A different potential application of Gaussian BosonSampling, first suggested by the Toronto-based startup Xanadu, is finding dense subgraphs in a graph. (Or at least, providing an initial seed to classical optimization methods that search for dense subgraphs.)

This is an NP-hard problem, so to say that I was skeptical of the proposal would be a gross understatement. Nevertheless, it turns out that there is a striking observation by the Xanadu team at the core of their proposal: namely that, given a graph G and a positive even integer k, a GBS device can be used to sample a random subgraph of G of size k, with probability proportional to the square of the number of perfect matchings in that subgraph. Cool, right? And potentially even useful, especially if the number of perfect matchings could serve as a rough indicator of the subgraph’s density! Alas, Xanadu’s Juan Miguel Arrazola himself recently told me that there’s a cubic-time classical algorithm for the same sampling task, so that the possible quantum speedup that one could get from GBS in this way is at most polynomial. The search for a useful application of BosonSampling continues!

And that’s all for now! I’m grateful to all the colleagues I talked to over the last couple weeks, including Alex Arkhipov, Juan Miguel Arrazola, Sergio Boixo, Raul Garcia-Patron, Leonid Gurvits, Gil Kalai, Chaoyang Lu, John Martinis, and Jelmer Renema, while obviously taking sole responsibility for any errors in the above. I look forward to a spirited discussion in the comments, and of course I’ll post updates as I learn more!

Professor Crystal Senko awarded Canada Research Chair in Trapped Ion Quantum Computing

12011 — Wed, 16 Dec 2020 00:00:00 +0000

Wednesday, December 16, 2020

It is with great pleasure that we congratulate Professor Crystal Senko of the Department of Physics & Astronomy and the Institute for Quantum Computing for being named a Canada Research Chair (CRC).