Quantum

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.

NVIDIA Announces SDK for Quantum Simulation on GPUs

dougfinke — Mon, 12 Apr 2021 18:56:13 +0000

One very useful tools for those wishing to develop quantum programs is a classical computing based simulator that can demonstrate how a quantum computer would process the program. Although the drawback of this approach is that it is limited to the number of qubits the classical computer can simulate, but it has the advantage is [...]

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Keysight Technologies Partners with Women in Quantum to Create a Mentoring Program and also Provides Support for Quantum Education

dougfinke — Sat, 10 Apr 2021 22:59:57 +0000

You may not recognize the name Keysight Technologies as a participant in the quantum industry. But perhaps you would recognize them if we told you they are a direct descendent of the original Hewlett-Packard (HP) company that was founded in a garage in Palo Alto, California in 1939. The original Hewlett-Package product line consisted of [...]

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IBM Releases New Version of Qiskit; Adds Additional Libraries for Natural Sciences and Machine Learning

dougfinke — Sat, 10 Apr 2021 18:12:06 +0000

IBM has released version 0.25 of its Qiskit quantum programming platform with the biggest changes related to a restructuring and extension of their application libraries. Previously they had introduced a package called Qiskit Aqua that included application modules for chemistry, AI, optimization and finance. Qiskit Aqua was a separate package independent of the core Qiskit [...]

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U.S. Air Force and NSF Award $1 Million in Grants to University of Massachusetts Lowell Professor

dougfinke — Fri, 09 Apr 2021 23:45:50 +0000

The grants were made in two separate early career awards to Professor Archana Kamal at the University of Massachusetts Lowell (UMASS Lowell). The first award from the Air Force Office of Scientific Research is for $450,000 over three years to study tunable quantum dissipation. The goal of this research is to correct quantum errors by [...]

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The Netherlands has Awarded €615 Million ($732M USD) to Quantum Delta NL for Quantum R&D

dougfinke — Fri, 09 Apr 2021 21:30:49 +0000

The award was provided by the Dutch Ministry of Economic Affairs and Climate Policy's National Growth Fund to Quantum Delta NL, a public-private partnership of tech companies, government agencies, and all major quantum research centers in the Netherlands. The goals for this award will be to train 2,000 researchers and engineers in quantum technology, scale [...]

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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. Duality, a Quantum Startup Accelerator, Launched in Chicago appeared first on Quantum Computing Report.

Quantum Xchange Expands their Quantum-Safe Encryption Product Line with Phio TX-D

dougfinke — Tue, 06 Apr 2021 15:22:26 +0000

We first reported on Quantum Xchange' flagship Phio TX product in October 2019 when they introduced the concept of providing extra security for encryption keys with a separate out-of-band symmetric key distribution system that is separate from the main data channel. This system can be compatible with other encryption technologies including physics-based QKD (Quantum Key [...]

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New computing algorithms expand the boundaries of a quantum future

lindseya — Mon, 05 Apr 2021 12:00:33 +0000

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!

How to Make Money with Quantum? Create Art with It!

dougfinke — Sat, 03 Apr 2021 23:19:30 +0000

Are you using a quantum computer for computational chemistry, finance applications, or optimizations? That's so 2020! Here's an example of a real avant-garde use of quantum technology that combines Quantum Computers, Quantum Neural Nets (QNN), Blockchains and Non-Fungible Tokens (NFT). A piece of artwork titled "Everettian vibrations" was created using this technology and this is [...]

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DARPA Announces Funding Opportunity for Quantum Benchmarking

dougfinke — Sat, 03 Apr 2021 20:38:17 +0000

The U.S. Defense Advanced Research Projects Agency (DARPA) has issued a Broad Agency Announcement (BAA) calling for proposals for research in the area of quantum benchmarking. Proposed research should quantify the long-term utility of quantum computers. In particular, proposed research should center around either (1) the creation of application-specific, hardware-agnostic benchmarks for quantum computer utility [...]

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Riken, Fujitsu Partner to Develop a Superconducting Quantum Computer

dougfinke — Sat, 03 Apr 2021 19:37:58 +0000

We previously reported on Fujitsu's intent to partner with Riken to research superconducting quantum computers and this week they have announced the formal launch of the project. The project is now called the RIKEN RQC - Fujitsu Collaboration Center and is located within the RIKEN Center for Quantum Computing in Wako, Saitama, Japan. The project [...]

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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.

Discovery of a mechanism for making superconductors more resistant to magnetic fields

Tue, 30 Mar 2021 13:24:46 +0000

Superconductivity is known to be easily destroyed by strong magnetic fields. Researchers have discovered that a superconductor with atomic-scale thickness can retain its superconductivity even when a strong magnetic field is applied to it. The team has also identified a new mechanism behind this phenomenon. These results may facilitate the development of superconducting materials resistant to magnetic fields and topological superconductors composed of superconducting and magnetic materials.

Topological protection of entangled two-photon light in photonic topological insulators

Tue, 30 Mar 2021 12:12:54 +0000

Researchers have revealed the necessary conditions for the robust transport of entangled states of two-photon light in photonic topological insulators, paving the way the towards noise-resistant transport of quantum information.

Optical fiber could boost power of superconducting quantum computers

Wed, 24 Mar 2021 17:54:38 +0000

The secret to building superconducting quantum computers with massive processing power may be an ordinary telecommunications technology - optical fiber. Physicists have measured and controlled a superconducting quantum bit (qubit) using light-conducting fiber instead of metal electrical wires, paving the way to packing a million qubits into a quantum computer rather than just a few thousand.

Semiconductor qubits scale in two dimensions

Wed, 24 Mar 2021 17:54:35 +0000

The heart of any computer, its central processing unit, is built using semiconductor technology, which is capable of putting billions of transistors onto a single chip. Now, researchers have shown that this technology can be used to build a two-dimensional array of qubits to function as a quantum processor. Their work is a crucial milestone for scalable quantum technology.

Novel thermometer can accelerate quantum computer development

Tue, 23 Mar 2021 12:47:26 +0000

Researchers have developed a novel type of thermometer that can simply and quickly measure temperatures during quantum calculations with extremely high accuracy. The breakthrough provides a benchmarking tool for quantum computing of great value - and opens up for experiments in the exciting field of quantum thermodynamics.

Machine learning shows potential to enhance quantum information transfer

Mon, 22 Mar 2021 15:29:37 +0000

New researchers demonstrated a machine learning approach that corrects quantum information in systems composed of photons, improving the outlook for deploying quantum sensing and quantum communications technologies on the battlefield.

Institute for Quantum Computing joins 50 – 30 challenge

12011 — Mon, 22 Mar 2021 00:00:00 +0000

Monday, March 22, 2021

The Institute for Quantum Computing (IQC) at the University of Waterloo is proud to announce our membership in the Innovation, Science and Economic Development Canada 50 – 30 Challenge. The 50 – 30 Challenge is a program between the Government of Canada, businesses and diversity organizations with a goal to achieve both gender parity and increased presence of underrepresented groups on boards and in senior levels of management.

QC ethics and hype: the call is coming from inside the house

Scott — Sun, 21 Mar 2021 01:18:54 +0000

For years, I’d sometimes hear discussions about the ethics of quantum computing research. Quantum ethics!

When the debates weren’t purely semantic, over the propriety of terms like “quantum supremacy” or “ancilla qubit,” they were always about chin-strokers like “but what if cracking RSA encryption gives governments more power to surveil their citizens? or what if only a few big countries or companies get quantum computers, thereby widening the divide between haves and have-nots?” Which, OK, conceivably these will someday be issues. But, besides barely depending on any specific facts about quantum computing, these debates always struck me as oddly safe, because the moral dilemmas were so hypothetical and far removed from us in time.

I confess I may have even occasionally poked fun when asked to expound on quantum ethics. I may have commented that quantum computers probably won’t kill anyone unless a dilution refrigerator tips over onto their head. I may have asked forgiveness for feeding custom-designed oracles to BQP and QMA, without first consulting an ethics committee about the long-term effects on those complexity classes.

Now fate has punished me for my flippancy. These days, I really do feel like quantum computing research has become an ethical minefield—but not for any of the reasons mentioned previously. What’s new is that millions of dollars are now potentially available to quantum computing researchers, along with equity, stock options, and whatever else causes “ka-ching” sound effects and bulging eyes with dollar signs. And in many cases, to have a shot at such riches, all an expert needs to do is profess optimism that quantum computing will have revolutionary, world-changing applications and have them soon. Or at least, not object too strongly when others say that.

Some of today’s rhetoric will of course remind people of the D-Wave saga, which first brought this blog to prominence when it began in earnest in 2007. Quantum computers, we hear now as then, will soon leave the Earth’s fastest supercomputers in the dust. They’re going to harness superposition to try all the exponentially many possible solutions at once. They’ll crack the Traveling Salesman Problem, and will transform machine learning and AI beyond recognition. Meanwhile, simulations of quantum systems will be key to solving global warming and cancer.

Despite the parallels, though, this new gold rush doesn’t feel to me like the D-Wave one, which seems in retrospect like just a little dry run. If I had to articulate what’s new in one sentence, it’s that this time “the call is coming from inside the house.” Many of the companies making wildly overhyped claims are recognized leaders of the field. They have brilliant quantum computing theorists and experimentalists on their staff with impeccable research records. Some of those researchers are among my best friends. And even when I wince at the claims of near-term applications, in many cases (especially with quantum simulation) the claims aren’t obviously false—we won’t know for certain until we try it and see! It’s genuinely gotten harder to draw the line between defensible optimism and exaggerations verging on fraud.

Indeed, this time around virtually everyone in QC is “complicit” to a greater or lesser degree. I, too, have accepted compensation to consult on quantum computing topics, to give talks at hedge funds, and in a few cases to serve as a scientific adviser to quantum computing startups. I tell myself that, by 2021 standards, this stuff is all trivial chump change—a few thousands of dollars here or there, to expound on the same themes that I already discuss free of charge on this blog. I actually get paid to dispel hype, rather than propagate it! I tell myself that I’ve turned my back on the orders of magnitude more money available to those willing to hitch their scientific reputations to the aspirations of this or that specific QC company. (Yes, this blog, and my desire to preserve its intellectual independence and credibility, might well be costing me millions!)

But, OK, some would argue that accepting any money from QC companies or QC investors just puts you at the top of a slope with unabashed snake-oil salesmen at the bottom. With the commercialization of our field that started around 2015, there’s no bright line anymore marking the boundary between pure scientific curiosity and the pursuit of filthy lucre; it’s all just points along a continuum. I’m not sure that these people are wrong.

As some of you might’ve seen already, IonQ, the trapped-ion QC startup that originated from the University of Maryland, is poised to have the first-ever quantum computing IPO—a so-called “SPAC IPO,” which while I’m a financial ignoramus, apparently involves merging with a shell company and thereby bypassing the SEC’s normal IPO rules. Supposedly they’re seeking $650 million in new funding and a $2 billion market cap. If you want to see what IonQ is saying about QC to prospective investors, click here. Lacking any choice in the matter, I’ll probably say more about these developments in a future post.

Meanwhile, PsiQuantum, the Palo-Alto-based optical QC startup, has said that it’s soon going to leave “stealth mode.” And Amazon, Microsoft, Google, IBM, Honeywell, and other big players continue making large investments in QC—treating it, at least rhetorically, not at all like blue-sky basic research, but like a central part of their future business plans.

All of these companies have produced or funded excellent QC research. And of course, they’re all heterogeneous, composed of individuals who might vehemently disagree with each other about the near- or long-term prospects of QC. And yet all of them have, at various times, inspired reflections in me like the ones in this post.

I regret that this post has no clear conclusion. I’m still hashing things out, solicing thoughts from my readers and friends. Speaking of which: this coming Monday, March 22, at 8-10pm US Eastern time, I’ve decided to hold a discussion around these issues on Clubhouse—my “grand debut” on that app, and an opportunity to see whether I like it or not! My friend Adam Brown will moderate the discussion; other likely participants will be John Horgan, George Musser, Michael Nielsen, and Matjaž Leonardis. If you’re on Clubhouse, I hope to see you there!

Better batteries start with basics -- and a big computer

Fri, 19 Mar 2021 22:39:45 +0000

Researchers ran quantum simulations to understand glycerol carbonate, a compound used in biodiesel and as a common solvent.

The girls in STEM: this is how we bridge the gender gap

tracym — Fri, 19 Mar 2021 21:15:13 +0000

From Vanity Fair, March 18, 2021: April is national STEM month in Italy. and Fermilab's Anna Grasselino is highlighted as a role model for young women in pursuit of a career in STEM.

Solving 'barren plateaus' is the key to quantum machine learning

Fri, 19 Mar 2021 16:54:14 +0000

Many machine learning algorithms on quantum computers suffer from the dreaded 'barren plateau' of unsolvability, where they run into dead ends on optimization problems.

Abel to win

Scott — Thu, 18 Mar 2021 03:19:46 +0000

Many of you will have seen the happy news today that Avi Wigderson and László Lovász share this year’s Abel Prize (which now contends with the Fields Medal for the highest award in pure math). This is only the second time that the Abel Prize has been given wholly or partly for work in theoretical computer science, after Szemerédi in 2012. See also the articles in Quanta or the NYT, which actually say most of what I would’ve said for a lay audience about Wigderson’s and Lovász’s most famous research results and their importance (except, no, Avi hasn’t yet proved P=BPP, just taken some major steps toward it…).

On a personal note, Avi was both my and my wife Dana’s postdoctoral advisor at the Institute for Advanced Study in Princeton. He’s been an unbelievably important mentor to both of us, as he’s been for dozens of others in the CS theory community. Back in 2007, I also had the privilege of working closely with Avi for months on our Algebrization paper. Now would be a fine time to revisit Avi’s Permanent Impact on Me (or watch the YouTube video), which is the talk I gave at IAS in 2016 on the occasion of Avi’s 60th birthday.

Huge congratulations to both Avi and László!

New quantum algorithm surpasses the QPE norm

Wed, 17 Mar 2021 13:45:58 +0000

Researchers refine quantum computer-ready algorithm to measure the vertical ionization energies of atoms and molecules within 0.1 eV of precision.

Researchers enhance quantum machine learning algorithms

Tue, 16 Mar 2021 15:22:44 +0000

Researchers found a way to automatically infer parameters used in an important quantum Boltzmann machine algorithm for machine learning applications.

Smart quantum technologies for secure communication

Tue, 16 Mar 2021 13:34:42 +0000

Researchers have introduced a smart quantum technology for the spatial mode correction of single photons. The authors exploit the self-learning and self-evolving features of artificial neural networks to correct the distorted spatial profile of single photons.

Professor De Francesco participates in SQMS at Fermi National Accelerator Laboratory

tracym — Mon, 15 Mar 2021 21:05:56 +0000

From La Nazione Pisa, March 15, 2021: The center directed by Fermilab’s Anna Grassellino has the task of developing a state-of-the-art quantum computer with unprecedented performances based on superconducting technologies.

Remote control for quantum emitters

Fri, 12 Mar 2021 14:57:55 +0000

Quantum technologies are enabled by precise control of the state and interactions of individual quantum objects. Physicists have now proposed a way to remotely control the state of individual quantum emitters. The underlying idea is based on chirped light pulses.

Long-delayed UT Austin Quantum Complexity Theory Student Project Showcase!

Scott — Thu, 11 Mar 2021 20:31:03 +0000

Back at MIT, whenever I taught my graduate course on Quantum Complexity Theory (see here for lecture notes), I had a tradition of showcasing the student projects on this blog: see here (Fall 2010), here (Fall 2012), here (Fall 2014). I was incredibly proud that, each time I taught, at least some of the projects led to publishable original research—sometimes highly significant research, like Paul Christiano’s work on quantum money (which led to my later paper with him), Shelby Kimmel’s work on quantum query complexity, Jenny Barry’s work on quantum partially observable Markov decision processes (“QOMDPs”), or Matt Coudron and Henry Yuen’s work on randomness expansion (which led to their later breakthrough in the subject).

Alas, after I moved to UT Austin, for some reason I discontinued the tradition of these blog-showcases—and inexcusably, I did this even though the wonderful new research results continued! Now that I’m teaching Quantum Complexity Theory at UT for the third time (via Zoom, of course), I decided that it was finally time to remedy this. To keep things manageable, this time I’m going to limit myself to research projects that began their lives in my course and that are already public on the arXiv (or in one case, that will soon be).

So please enjoy the following smorgasbord, from 2016 and 2019 iterations of my course! And if you have any questions about any of the projects—well, I’ll try to get the students to answer in the comments section! Thanks so much and congratulations to the students for their work.

From the Fall 2016 iteration of the course

William Hoza (project turned into a joint paper with Cole Graham), Universal Bell Correlations Do Not Exist.

We prove that there is no finite-alphabet nonlocal box that generates exactly those correlations that can be generated using a maximally entangled pair of qubits. More generally, we prove that if some finite-alphabet nonlocal box is strong enough to simulate arbitrary local projective measurements of a maximally entangled pair of qubits, then that nonlocal box cannot itself be simulated using any finite amount of entanglement. We also give a quantitative version of this theorem for approximate simulations, along with a corresponding upper bound.

Patrick Rall, Signed quantum weight enumerators characterize qubit magic state distillation.

Many proposals for fault-tolerant quantum computation require injection of ‘magic states’ to achieve a universal set of operations. Some qubit states are above a threshold fidelity, allowing them to be converted into magic states via ‘magic state distillation’, a process based on stabilizer codes from quantum error correction.
We define quantum weight enumerators that take into account the sign of the stabilizer operators. These enumerators completely describe the magic state distillation behavior when distilling T-type magic states. While it is straightforward to calculate them directly by counting exponentially many operator weights, it is also an NP-hard problem to compute them in general. This suggests that finding a family of distillation schemes with desired threshold properties is at least as hard as finding the weight distributions of a family of classical codes.
Additionally, we develop search algorithms fast enough to analyze all useful 5 qubit codes and some 7 qubit codes, finding no codes that surpass the best known threshold.

From the Spring 2019 iteration of the course

Ying-Hao Chen, 2-Local Hamiltonian with Low Complexity is QCMA-complete.

We prove that 2-Local Hamiltonian (2-LH) with Low Complexity problem is QCMA-complete by combining the results from the QMA-completeness of 2-LH and QCMA-completeness of 3-LH with Low Complexity. The idea is straightforward. It has been known that 2-LH is QMA-complete. By putting a low complexity constraint on the input state, we make the problem QCMA. Finally, we use similar arguments as in [Kempe, Kitaev, Regev] to show that all QCMA problems can be reduced to our proposed problem.

Jeremy Cook, On the relationships between Z-, C-, and H-local unitaries.

Quantum walk algorithms can speed up search of physical regions of space in both the discrete-time [arXiv:quant-ph/0402107] and continuous-time setting [arXiv:quant-ph/0306054], where the physical region of space being searched is modeled as a connected graph. In such a model, Aaronson and Ambainis [arXiv:quant-ph/0303041] provide three different criteria for a unitary matrix to act locally with respect to a graph, called Z-local, C-local, and H-local unitaries, and left the open question of relating these three locality criteria. Using a correspondence between continuous- and discrete-time quantum walks by Childs [arXiv:0810.0312], we provide a way to approximate N×N H-local unitaries with error δ using O(1/√δ,√N) C-local unitaries, where the comma denotes the maximum of the two terms.

Joshua A. Cook, Approximating Unitary Preparations of Orthogonal Black Box States.

In this paper, I take a step toward answering the following question: for m different small circuits that compute m orthogonal n qubit states, is there a small circuit that will map m computational basis states to these m states without any input leaving any auxiliary bits changed. While this may seem simple, the constraint that auxiliary bits always be returned to 0 on any input (even ones besides the m we care about) led me to use sophisticated techniques. I give an approximation of such a unitary in the m = 2 case that has size polynomial in the approximation error, and the number of qubits n.

Sabee Grewal (project turned into a joint paper with me), Efficient Learning of Non-Interacting Fermion Distributions.

We give an efficient classical algorithm that recovers the distribution of a non-interacting fermion state over the computational basis. For a system of n non-interacting fermions and m modes, we show that O(m²n⁴log(m/δ)/ε⁴) samples and O(m⁴n⁴log(m/δ)/ε⁴) time are sufficient to learn the original distribution to total variation distance ε with probability 1−δ. Our algorithm empirically estimates the one- and two-mode correlations and uses them to reconstruct a succinct description of the entire distribution efficiently.

Sam Gunn and Niels Kornerup, Review of a Quantum Algorithm for Betti Numbers.

We looked into the algorithm for calculating Betti numbers presented by Lloyd, Garnerone, and Zanardi (LGZ). We present a new algorithm in the same spirit as LGZ with the intent of clarifying quantum algorithms for computing Betti numbers. Our algorithm is simpler and slightly more efficient than that presented by LGZ. We present a thorough analysis of our algorithm, pointing out reasons that both our algorithm and that presented by LGZ do not run in polynomial time for most inputs. However, the algorithms do run in polynomial time for calculating an approximation of the Betti number to polynomial multiplicative error, when applied to some class of graphs for which the Betti number is exponentially large.

William Kretschmer, Lower Bounding the AND-OR Tree via Symmetrization.

We prove a simple, nearly tight lower bound on the approximate degree of the two-level AND-OR tree using symmetrization arguments. Specifically, we show that ~deg(ANDm∘ORn)=Ω(~√(mn)). To our knowledge, this is the first proof of this fact that relies on symmetrization exclusively; most other proofs involve the more complicated formulation of approximate degree as a linear program [BT13, She13, BDBGK18]. Our proof also demonstrates the power of a symmetrization technique involving Laurent polynomials (polynomials with negative exponents) that was previously introduced by Aaronson, Kothari, Kretschmer, and Thaler [AKKT19].

Jiahui Liu and Ruizhe Zhang (project turned into a joint paper with me, Mark Zhandry, and Qipeng Liu),
New Approaches for Quantum Copy-Protection.

Quantum copy protection uses the unclonability of quantum states to construct quantum software that provably cannot be pirated. Copy protection would be immensely useful, but unfortunately little is known about how to achieve it in general. In this work, we make progress on this goal, by giving the following results:
– We show how to copy protect any program that cannot be learned from its input/output behavior, relative to a classical oracle. This improves on Aaronson [CCC’09], which achieves the same relative to a quantum oracle. By instantiating the oracle with post-quantum candidate obfuscation schemes, we obtain a heuristic construction of copy protection.
– We show, roughly, that any program which can be watermarked can be copy detected, a weaker version of copy protection that does not prevent copying, but guarantees that any copying can be detected. Our scheme relies on the security of the assumed watermarking, plus the assumed existence of public key quantum money. Our construction is general, applicable to many recent watermarking schemes.

John Kallaugher, Triangle Counting in the Quantum Streaming Model. Not yet available but coming soon to an arXiv near you!

We give a quantum algorithm for counting triangles in graph streams that uses less space than the best possible classical algorithm.

Breakthrough lays groundwork for future quantum networks

Thu, 11 Mar 2021 19:20:41 +0000

New research could help lay the groundwork for future quantum communication networks and large-scale quantum computers.

Robots learn faster with quantum technology

Thu, 11 Mar 2021 17:34:32 +0000

Artificial intelligence is part of our modern life. A crucial question for practical applications is how fast such intelligent machines can learn. An experiment has answered this question, showing that quantum technology enables a speed-up in the learning process. The physicists have achieved this result by using a quantum processor for single photons as a robot.

Sayonara Majorana?

Scott — Wed, 10 Mar 2021 22:29:51 +0000

Many of you have surely already seen the news that the Kouwenhoven group in Delft—which in 2018 published a paper in Nature claiming to have detected Majorana fermions, a type of nonabelian anyon—have retracted the paper and apologized for “insufficient scientific rigour.” This work was considered one of the linchpins of Microsoft’s experimental effort toward building topological quantum computers.

Like most quantum computing theorists, I guess, I’m thrilled if Majorana fermions can be created using existing technology, I’m sad if they can’t be, but I don’t have any special investment in or knowledge of the topic, beyond what I read in the news or hear from colleagues. Certainly Majorana fermions seem neither necessary nor sufficient for building a scalable quantum computer, although they’d be a step forward for the topological approach to QC.

The purpose of this post is to invite informed scientific discussion of the relevant issues—first and foremost so that I can learn something, and second so that my readers can! I’d be especially interested to understand:

Weren’t there, like, several other claims to have produced Majorana fermions? What of those then?
If, today, no one has convincingly demonstrated the existence of Majoranas, then do people think it more likely that they were produced but not detected, or that they weren’t even produced?
How credible are the explanations as to what went wrong?
Are there any broader implications for the prospects of topological QC, or Microsoft’s path to topological QC, or was this just an isolated mistake?

Finding quvigints in a quantum treasure map

Wed, 10 Mar 2021 17:25:24 +0000

Researchers have struck quantum gold -- and created a new word -- by enlisting machine learning to efficiently navigate a 20-dimensional quantum treasure map.

Superconducting Quantum Materials and Systems Center in Chicago University, the scientist Anna Grassellino inaugurates the teaching of the second semester

tracym — Tue, 09 Mar 2021 15:05:20 +0000

From La Nazione, March 8, 2021: Fermilab’s Anna Grassellino will inaugurate second semester teaching at the University of Pisa at 4 pm on Wednesday 10 March, live streaming on the social channels of the Pisa University.

Another axe swung at the Sycamore

Scott — Sun, 07 Mar 2021 19:15:53 +0000

So there’s an interesting new paper on the arXiv by Feng Pan and Pan Zhang, entitled “Simulating the Sycamore supremacy circuits.” It’s about a new tensor contraction strategy for classically simulating Google’s 53-qubit quantum supremacy experiment from Fall 2019. Using their approach, and using just 60 GPUs running for a few days, the authors say they managed to generate a million correlated 53-bit strings—meaning, strings that all agree on a specific subset of 20 or so bits—that achieve a high linear cross-entropy score.

Alas, I haven’t had time this weekend to write a “proper” blog post about this, but several people have by now emailed to ask my opinion, so I thought I’d share the brief response I sent to a journalist.

This does look like a significant advance on simulating Sycamore-like random quantum circuits! Since it’s based on tensor networks, you don’t need the literally largest supercomputer on the planet filling up tens of petabytes of hard disk space with amplitudes, as in the brute-force strategy proposed by IBM. Pan and Zhang’s strategy seems most similar to the strategy previously proposed by Alibaba, with the key difference being that the new approach generates millions of correlated samples rather than just one.

I guess my main thoughts for now are:

Once you knew about this particular attack, you could evade it and get back to where we were before by switching to a more sophisticated verification test — namely, one where you not only computed a Linear XEB score for the observed samples, you also made sure that the samples didn’t share too many bits in common. (Strangely, though, the paper never mentions this point.)
The other response, of course, would just be to redo random circuit sampling with a slightly bigger quantum computer, like the ~70-qubit devices that Google, IBM, and others are now building!

Anyway, very happy for thoughts from anyone who knows more.

New quantum theory heats up thermodynamic research

Fri, 05 Mar 2021 13:01:15 +0000

Researchers have developed a new quantum version of a 150-year-old thermodynamical thought experiment that could pave the way for the development of quantum heat engines.

The Zen Anti-Interpretation of Quantum Mechanics

Scott — Thu, 04 Mar 2021 23:26:29 +0000

As I lay bedridden this week, knocked out by my second dose of the Moderna vaccine, I decided I should blog some more half-baked ideas because what the hell? It feels therapeutic, I have tenure, and anyone who doesn’t like it can close their broswer tab.

So: although I’ve written tens of thousands of words, on this blog and elsewhere, about interpretations of quantum mechanics, again and again I’ve dodged the question of which interpretation (if any) I really believe myself. Today, at last, I’ll emerge from the shadows and tell you precisely where I stand.

I hold that all interpretations of QM are just crutches that are better or worse at helping you along to the Zen realization that QM is what it is and doesn’t need an interpretation. As Sidney Coleman famously argued, what needs reinterpretation is not QM itself, but all our pre-quantum philosophical baggage—the baggage that leads us to demand, for example, that a wavefunction |ψ⟩ either be “real” like a stubbed toe or else “unreal” like a dream. Crucially, because this philosophical baggage differs somewhat from person to person, the “best” interpretation—meaning, the one that leads most quickly to the desired Zen state—can also differ from person to person. Meanwhile, though, thousands of physicists (and chemists, mathematicians, quantum computer scientists, etc.) have approached the Zen state merely by spending decades working with QM, never worrying much about interpretations at all. This is probably the truest path; it’s just that most people lack the inclination, ability, or time.

Greg Kuperberg, one of the smartest people I know, once told me that the problem with the Many-Worlds Interpretation is not that it says anything wrong, but only that it’s “melodramatic” and “overwritten.” Greg is far along the Zen path, probably further than me.

You shouldn’t confuse the Zen Anti-Interpretation with “Shut Up And Calculate.” The latter phrase, mistakenly attributed to Feynman but really due to David Mermin, is something one might say at the beginning of the path, when one is as a baby. I’m talking here only about the endpoint of path, which one can approach but never reach—the endpoint where you intuitively understand exactly what a Many-Worlder, Copenhagenist, or Bohmian would say about any given issue, and also how they’d respond to each other, and how they’d respond to the responses, etc. but after years of study and effort you’ve returned to the situation of the baby, who just sees the thing for what it is.

Let no one misinterpret me as saying that the interpretations are all interchangeable, or equally good or bad. If you had to, you could call even me a “Many-Worlder,” but only in the following limited sense: that in fifteen years of teaching quantum information, my experience has consistently been that for most students, Everett’s crutch is the best currently on the market. At any rate, it’s the one that’s most like a straightforward picture of the equations, and least like a wobbly tower of words that might collapse if you utter the wrong ones. Unlike Bohr, Everett will never make you feel stupid for asking the questions an inquisitive child would; he’ll simply tell you answers that are as clear, logical, and internally consistent as they are metaphysically extravagant. That’s a start.

The Copenhagen Interpretation retains a place of honor as the first crutch, for decades the only crutch, and the one closest to the spirit of positivism. Unfortunately, wielding the Copenhagen crutch requires mad philosophical skillz—which parts of the universe should you temporarily regard as “classical”? which questions should be answered, and which deflected?—to the point where, if you’re capable of all that verbal footwork, then why do you even need a crutch in the first place? In the hands of an amateur—meaning, nearly everyone—Copenhagen can lead away from rather than toward the Zen state, as one sees with the generations of New-Agey bastardizations about “observations creating reality.”

As for deBroglie-Bohm—that’s a weird, interesting, baroque crutch, one whose actual details (the preferred basis and the guiding equation) are historically contingent and tied to specific physical systems. It’s probably the right crutch for someone—it gets eternal credit for having led Bell to discover the Bell inequality—but its quirks definitely need to be discarded along the way.

Note that, among those who approach the Zen state, many still call themselves Many-Worlders or Copenhagenists or Bohmians or whatever—just like those far along in spiritual enlightenment might still call themselves Buddhists or Catholics or Muslims or Jews (or atheists or agnostics)—even though, by that point, they might have more in common with each other than they do with their supposed coreligionists or co-irreligionists.

Alright, but isn’t all this Zen stuff just a way to dodge the actual, substantive questions about QM, by cheaply claiming to have transcended them? If that’s your charge, then please help yourself to the following FAQ about the details of the Zen Anti-Interpretation.

What is a quantum state? It’s a unit vector of complex numbers (or if we’re talking about mixed states, then a trace-1, Hermitian, positive semidefinite matrix), which encodes everything there is to know about a physical system.
OK, but are the quantum states “ontic” (really out in the world), or “epistemic” (only in our heads)? Dude. Do “basketball games” really exist, or is that just a phrase we use to summarize our knowledge about certain large agglomerations of interacting quarks and leptons? Do even the “quarks” and “leptons” exist, or are those just words for excitations of the more fundamental fields? Does “jealousy” exist? Pretty much all our concepts are complicated grab bags of “ontic” and “epistemic,” so it shouldn’t surprise us if quantum states are too. Bad dichotomy.
Why are there probabilities in QM? Because QM is a (the?) generalization of probability theory to involve complex numbers, whose squared absolute values are probabilities. It includes probability as a special case.
But why do the probabilities obey the Born rule? Because, once the unitary part of QM has picked out the 2-norm as being special, for the probabilities also to be governed by the 2-norm is pretty much the only possibility that makes mathematical sense; there are many nice theorems formalizing that intuition under reasonable assumptions.
What is an “observer”? It’s exactly what modern decoherence theory says it is: a particular kind of quantum system that interacts with other quantum systems, becomes entangled with them, and thereby records information about them—reversibly in principle but irreversibly in practice.
Can observers be manipulated in coherent superposition, as in the Wigner’s Friend scenario? If so, they’d be radically unlike any physical system we’ve ever had direct experience with. So, are you asking whether such “observers” would be conscious, or if so what they’d be conscious of? Who the hell knows?
Do “other” branches of the wavefunction—ones, for example, where my life took a different course—exist in the same sense this one does? If you start with a quantum state for the early universe and then time-evolve it forward, then yes, you’ll get not only “our” branch but also a proliferation of other branches, in the overwhelming majority of which Donald Trump was never president and civilization didn’t grind to a halt because of a bat near Wuhan. But how could we possibly know whether anything “breathes fire” into the other branches and makes them real, when we have no idea what breathes fire into this branch and makes it real? This is not a dodge—it’s just that a simple “yes” or “no” would fail to do justice to the enormity of such a question, which is above the pay grade of physics as it currently exists.
Is this it? Have you brought me to the end of the path of understanding QM? No, I’ve just pointed the way to the beginning of the path. The most fundamental tenet of the Zen Anti-Interpretation is that there’s no shortcut to actually working through the Bell inequality, quantum teleportation, Shor’s algorithm, the Kochen-Specker and PBR theorems, possibly even a photon or hydrogen atom, so you see quantum probability in action. I’m further along the path than I was twenty years ago, but not as far along as some of my colleagues. Even the greatest quantum Zen masters will be able to get further when new quantum phenomena and protocols are discovered in the future. All the same, though—and this is another major teaching of the Zen Anti-Interpretation—there’s more to life than achieving greater and greater clarity about the foundations of QM. And on that note…

To those who asked me about Claus Peter Schnorr’s claim to have discovered a fast classical factoring algorithm, thereby “destroying” (in his words) the RSA cryptosystem, see (e.g.) this Twitter thread by Keegan Ryan, which explains what certainly looks like a fatal error in Schnorr’s paper.

'Egg carton' quantum dot array could lead to ultralow power devices

Thu, 04 Mar 2021 17:53:24 +0000

A new path toward sending and receiving information with single photons of light has been discovered by an international team of researchers.

Quantum Shorts festival announces three film winners

12011 — Thu, 04 Mar 2021 00:00:00 +0000

Thursday, March 4, 2021

“I am Andra. Number 2342. In a few hours I will cease to exist,” opens the short film Gods. The futuristic fantasy film, bringing us the last message of a civilisation that deciphered the secrets of quantum physics, has taken First Prize in the Quantum Shorts festival.

Heat-free optical switch would enable optical quantum computing chips

Wed, 03 Mar 2021 19:24:56 +0000

In a potential boost for quantum computing and communication, a European research collaboration reported a new method of controlling and manipulating single photons without generating heat. The solution makes it possible to integrate optical switches and single-photon detectors in a single chip.

A quantum internet is closer to reality, thanks to this switch

Tue, 02 Mar 2021 20:42:36 +0000

When quantum computers become more powerful and widespread, they will need a robust quantum internet to communicate. Engineers have addressed an issue barring the development of quantum networks that are big enough to reliably support more than a handful of users.

Quantum quirk yields giant magnetic effect, where none should exist

Fri, 26 Feb 2021 19:04:53 +0000

In a twist befitting the strange nature of quantum mechanics, physicists have discovered the Hall effect -- a characteristic change in the way electricity is conducted in the presence of a magnetic field -- in a nonmagnetic quantum material to which no magnetic field was applied.