Fresh from ETH Zurich comes the new Silq programming language. They also have submitted a paper to the PLDI 2020 conference on why they feel that it is the best quantum programming language so far. Although it may be not common knowledge, the lack of usable general purpose quantum computers has not kept multiple teams from developing programming languages for such computer systems.
Microsoft’s Q# is a strong contender in this space, along with the older QCL language. The claims by the Silq team on exactly why their language is better appear to come down to it being ‘more high level’, and by supporting automatic (and safe) uncomputation. While the ‘high level’ aspect is suspect since Q# is most decidedly a high-level programming language, their uncomputation claim does at least have some merit.
Uncomputation is a concept in quantum programming, where one occasionally has to remove a few intermediate objects from the current state because they may cause quantum interference that would affect the resulting output. Normally, one would save the intermediate result to a register for this, then reset the state and continue. Which parts of the state to keep and what to uncompute is however not easily determined, as a quick glance at related answers over at the Quantum Computing StackExchange and Theoretical Computer Science might reveal.
The main question thus appears the validity of this claim about Silq being able to automatically determine what ‘garbage’ can be safely uncomputed, and what should be part of the quantum interference. We have all seen with languages like Java and C# how even with traditional computing something as simple as garbage collecting can go horribly wrong. Maybe we shouldn’t count our quantum chickens yet until this particular waveform has fully collapsed.
Everyone learns differently, but cognitive research shows that you tend to remember things better if you use spaced repetition. That is, you learn something, then after a period, you are tested. If you still remember, you get tested again later with a longer interval between tests. If you get it wrong, you get tested earlier. That’s the idea behind [Andy Matuschak ‘s]and [Michael Nielsen’s] quantum computing tutorial. You answer questions embedded in the text. You answer to yourself, so there’s no scoring. However, once you click to reveal the answer, you report if you got the answer correct or not, and the system schedules you for retest based on your report.
Does it work? We don’t know, but we have heard that spaced repetition is good for learning languages, among other things. We suspect that like most learning methods, it works better for some people than others.
Quantum computers stand a good chance of changing the face computing, and that goes double for encryption. For encryption methods that rely on the fact that brute-forcing the key takes too long with classical computers, quantum computing seems like its logical nemesis.
For instance, the mathematical problem that lies at the heart of RSA and other public-key encryption schemes is factoring a product of two prime numbers. Searching for the right pair using classical methods takes approximately forever, but Shor’s algorithm can be used on a suitable quantum computer to do the required factorization of integers in almost no time.
When quantum computers become capable enough, the threat to a lot of our encrypted communication is a real one. If one can no longer rely on simply making the brute-forcing of a decryption computationally heavy, all of today’s public-key encryption algorithms are essentially useless. This is the doomsday scenario, but how close are we to this actually happening, and what can be done?
Modern physics experiments are often complex, ambitious, and costly. The times where scientific progress could be made by conducting a small tabletop experiment in your lab are mostly over. Especially, in fields like astrophysics or particle physics, you need huge telescopes, expensive satellite missions, or giant colliders run by international collaborations with hundreds or thousands of participants. To drive this point home: the largest machine ever built by humankind is the Large Hadron Collider (LHC). You won’t be surprised to hear that even just managing the data it produces is a super-sized task.
Since its start in 2008, the LHC at CERN has received several upgrades to stay at the cutting edge of technology. Currently, the machine is in its second long shutdown and being prepared to restart in May 2021. One of the improvements of Run 3 will be to deliver particle collisions at a higher rate, quantified by the so-called luminosity. This enables experiments to gather more statistics and to better study rare processes. At the end of 2024, the LHC will be upgraded to the High-Luminosity LHC which will deliver an increased luminosity by up to a factor of 10 beyond the LHC’s original design value.
Currently, the major experiments ALICE, ATLAS, CMS, and LHCb are preparing themselves to cope with the expected data rates in the range of Terabytes per second. It is a perfect time to look into more detail at the data acquisition, storage, and analysis of modern high-energy physics experiments. Continue reading “Crunching Giant Data From The Large Hadron Collider”→
It has been a while since we thought about computers and thought about Honeywell. Sure, they had a series of computers they bought from General Electric and Computer Control Company in the 1970s. Even before that they joined with Raytheon and produced vacuum tube computers that later morphed into transistor-based computers. But in recent years, you are more likely to think of Honeywell for thermostats, air filters, and industrial controls. But now, Honeywell has come out of the computer shadows with some impressive quantum computer hardware and they clearly have big plans.
Comparing quantum computers is a bit dicey just as, for example, judging CPUs by instructions per second has its problems. In the past, vendors have jockeyed for the maximum number of qubits, but that’s misleading in some cases. Processing power depends on the number of qubits, their quality, and how they are connected. IBM introduced the idea of quantum volume and Honeywell claims their new machine will hit 64 by that measure, twice that of anyone else’s quantum computer that we know about.
In any normal situation, if you’d read an article that about building your own quantum computer, a fully understandable and natural reaction would be to call it clickbaity poppycock. But an event like the Chaos Communication Congress is anything but a normal situation, and you never know who will show up and what background they will come from. A case in point: security veteran [Yann Allain] who is in fact building his own quantum computer in his garage.
Starting with an introduction to quantum computing itself, and what makes it so powerful also in the context of security, [Yann] continues to tell about his journey of building a quantum computer on his own. His goal was to build a stable computer he could “easily” create by himself in his garage, which will work at room temperature, using trapped ion technology. After a few iterations, he eventually created a prototype with KiCad that he cut into an empty ceramic chip carrier with a hobbyist CNC router, which will survive when placed in a vacuum chamber. While he is still working on a DIY laser system, he feels confident to be on the right track, and his estimate is that his prototype will achieve 10-15 qubits with a single ion trap, aiming to chain several ion traps later on.
As quantum computing is often depicted as cryptography’s doomsday device, it’s of course of concern that someone might just build one in their garage, but in order to improve future cryptographic systems, it also requires to fully understand — also on a practical level — quantum computing itself. Whether you want to replicate one yourself, at a rough cost of “below 15k Euro so far” is of course a different story, but who knows, maybe [Yann] might become the Josef Prusa of quantum computers one day.
Ever wondered what “cyberwar” looks like? Apparently it’s a lot of guessing security questions and changing passwords. It’s an interesting read on its own, but there are some interesting clues if you read between the lines. A General in the know mentioned that Isis:
clicked on something or they did something that then allowed us to gain control and then start to move.
This sounds very similar to stories we’ve covered in the past, where 0-days are used to compromise groups or individuals. Perhaps the NSA supplied such an exploit, and it was sent in a phishing attack. Through various means, the U.S. team quietly compromised systems and collected credentials.
The article mentions something else interesting. Apparently the targets of this digital sting had also been compromising machines around the world, and using those machines to manage their efforts. The decision was made by the U.S. team to also compromise those machines, in order to lock out the Isis team. This might be the most controversial element of the story. Security researchers have wanted permission to do this for years. How should the third parties view these incursions?