Quantum Inspired Algorithm Going Back To The Source

Recently, [Jabrils] set out to accomplish a difficult task: porting a quantum-inspired algorithm to run on a (simulated) quantum computer. Algorithms are often inspired by all sorts of natural phenomena. For example, a solution to the traveling salesman problem models ants and their pheromone trails. Another famous example is neural nets, which are inspired by the neurons in your brain. However, attempting to run a machine learning algorithm on your neurons, even with the assistance of pen and paper would be a nearly impossible exercise.

The quantum-inspired algorithm in question is known as the wavefunction collapse function. In a nutshell, you have a cube of voxels, a graph of nodes, or simply a grid of tiles as well as a list of detailed rules to determine the state of a node or tile. At the start of the algorithm, each node or point is considered in a state of superposition, which means it is considered to be in every possible state. Looking at the list of rules, the algorithm then begins to collapse the states. Unlike a quantum computer, states of superposition is not an intrinsic part of a classic computer, so this solving must be done iteratively. In order to reduce possible conflicts and contradictions later down the line, the nodes with the least entropy (the smallest number of possible states) are solved first. At first, random states are assigned, with the changes propagating through the system. This process is continued until the waveform is ultimately collapsed to a stable state or a contradiction is reached.

What’s interesting is that the ruleset doesn’t need to be coded, it can be inferred from an example. A classic use case of this algorithm is 2D pixel-art level design. By providing a small sample level, the algorithm churns and produces similar but wholly unique output. This makes it easy to provide thousands of unique and beautiful levels from an easy source image, however it comes at a price. Even a small level can take hours to fully collapse. In theory, a quantum computer should be able to do this much faster, since after all, it was the inspiration for this algorithm in the first place.

[Jabrils] spent weeks trying to get things running but ultimately didn’t succeed. However, his efforts give us a peek into the world of quantum computing and this amazing algorithm. We look forward to hearing more about this project from [Jabrils] who is continuing to work on it in his spare time. Maybe give it a shot yourself by learning the basics of quantum computing for yourself.

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Duality Of Light Explored By Revisiting The Double-Slit Experiment

We’ve all seen recreations of the famous double-slit experiment, which showed that light can behave both as a wave and as a particle. Or rather, it’s likely that what we’ve seen is the results of the double-slit experiment, that barcode-looking pattern of light and dark stripes, accompanied by some handwaving about classical versus quantum mechanics. But if you’ve got 20 minutes to invest, this video of the whole double-slit experiment cuts through the handwaving and opens your eyes to the quantum world.

For anyone unfamiliar with the double-slit experiment,¬† [Huygens Optics] actually doesn’t spend that much time explaining the background. Our explainer does a great job on the topic, but suffice it to say that when coherent light passes through two closely spaced, extremely fine openings, a characteristic pattern of alternating light and dark bands can be observed. On the one hand, this demonstrates the wave nature of light, just as waves on the ocean or sound waves interfere constructively and destructively. On the other hand, the varying intensity across the interference pattern suggests a particle nature to light.

To resolve this conundrum, [Huygens] jumps right into the experiment, which he claims can be done with simple, easily sourced equipment. This is belied a little by the fact that he used photolithography to create his slits, but it should still be possible to reproduce with slits made in more traditional ways. The most fascinating bit of this for us was the demonstration of single-photon self-interference using nothing but neutral density filters and a CCD camera. The explanation that follows of how it can be that a single photon can pass through both slits at the same time is one of the most approachable expositions on quantum mechanics we’ve ever heard.

[Huygens Optics] has done some really fascinating stuff lately, from variable profile mirrors to precision spirit levels. This one, though, really helped scratch our quantum itch.

Burning Things With Big Lasers In The Name Of Security

Several fields of quantum research have made their transition from research labs into commercial products, accompanied by grandiose claims. Are they as good as they say? We need people like Dr. Sarah Kaiser to independently test those claims, looking for flaws in implementation. At the 2019 Hackaday Superconference she shared her research on attacking commercially available quantum key distribution (QKD) hardware.

Don’t be scared away when you see the term “quantum” in the title. Her talk is very easy to follow along, requiring almost no prior knowledge of quantum research terminology. In fact, that’s the point. Dr. Kaiser’s personal ambition is to make quantum computing an inviting and accessible topic for everyone, not just elite cliques of researchers in ivory towers. You should hear her out in the video below, and by following along with the presentation slide deck (.PPTX).

Quantum Key Distribution

So why is QKD is so enticing? Unlike existing methods, the theoretical foundation is secure against any attacker constrained by the speed of light and the laws of physics.

Generally speaking, if your attacker is not bound by those things, we have a much bigger problem.

But as we know well, there’s always a difference between the theoretical foundation and the actual implementation of cryptography. That difference is where exploits like side-channel attacks thrive, so she started investigating components of a laser QKD system.

As a self-professed “Crazy Laser Lady”, part of this investigation examined how components held up to big lasers delivering power far outside normal operating range. This turned up exciting effects like a fiber fuse (~17:30 in the video) which is actually a plasma fire propagating through the fiber optic. It looks cool, but it’s destructive and useless for covert attacks. More productive results came when lasers were used to carefully degrade select components to make the system vulnerable.

If you want to learn more from Dr. Kaiser about quantum key distribution, she has a book chapter on the topic. (Free online access available, but with limitations.) This is not the first attempt to hack quantum key distribution, and we doubt it would be the last. Every generation of products will improve tolerance to attacks, and we’ll need researchers like our Crazy Laser Lady to find the reality behind advertised claims.

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Quantum Radar Hides In Plain Sight

Radar was a great invention that made air travel much safer and weather prediction more accurate, indeed it is even credited with winning the Battle of Britain. However, it carries a little problem with it during times of war. Painting a target with radar (or even sonar) is equivalent to standing up and wildly waving a red flag in front of your enemy, which is why for example submarines often run silent and only listen, or why fighter aircraft often rely on guidance from another aircraft. However, researchers in Italy, the UK, the US, and Austria have built a proof-of-concept radar that is very difficult to detect which relies upon quantum entanglement.

Despite quantum physics being hard to follow, the concept for the radar is pretty easy to understand. First, they generate an entangled pair of microwave photons, a task they perform with a Josephson phase converter. Then they store an “idle” photon while sending the “signal” photon out into the world. Detecting a single photon coming back is prone to noise, but in this case detecting the signal photon disturbs the idle photon and is reasonably easy to detect. It is likely that the entanglement will no longer be intact by the time of the return, but the correlation between the two photons remains detectable.

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Noise: It Turns Out You Need It

We don’t know whether quantum physics proves the universe is truly a strange place or that we are living in a virtual reality simulation, but we know it turns a lot of common sense into garbage. Take noise, for example. Noise — as in random electrical noise — is bad, right? We spend a lot of time designing to minimize noise. Researchers in Austria, Germany, and Australia recently published a paper that shows that noise can actually improve the flow of energy. While the paper is behind a paywall, the Focus article is available and, of course, you can probably find a copy of the paper if you want to read the entire thing.

The paper, titled “Environment-Assisted Quantum Transport in a 10-qubit Network” uses trapped calcium atoms to study an effect suspected of being a key factor in high-efficiency energy transfer such as the transfer observed in optical fibers and photosynthesis.

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Quantum Computing For Computer Scientists

Quantum computing is coming, so a lot of people are trying to articulate why we want it and how it works. Most of the explanations are either hardcore physics talking about spin and entanglement, or very breezy and handwaving which can be useful to get a little understanding but isn’t useful for applying the technology. Microsoft Research has a video that attempts to hit that spot in the middle — practical information for people who currently work with traditional computers. You can see the video below.

The video starts with basics you’d get from most videos talking about vector representation and operations. You have to get through about 17 minutes of that sort of thing until you get into qubits. If you glaze over on math, listen to the “index array” explanations [Andrew] gives after the math and you’ll be happier.

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Simple Quantum Computing In 150 Lines Of Python

What does it take to build a quantum computer? Lots of exotic supercooled hardware. However, creating a simulator isn’t nearly as hard and can give you a lot of insight into how this kind of computing works. A simulator doesn’t even have to be complicated. Here’s one that exists in about 150 lines of Python code.

You might wonder what the value is. After all, there are plenty of well-done simulators including Quirk that we have looked at in the past. What’s charming about this simulator is that with only 150 lines of code, you can reasonably read the whole thing in a sitting and gain an understanding of how the different operations really affect the state.

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