I have access to friends working directly on the hardware RnD at one of the main players. When I ask if how close we are to q-day the answer is always
well....ummm...............you see.........we are really happy with the progress we made so far and continue to make more progress.
something like that anyway. Not a single one ever says yeah real soon or defiantly by this date. The people that work there on other things basically laugh and say probably never but its an interesting job. To me Q-day is the same as every research stage tech, somewhere between tomorrow and never.
Disclaimer I never used the term q-day before but am adopting it for ease of commenting.
We need to prepare for it but there are still a few elements that still need to be worked on. Capacity and size of machine are two major issues at the moment that are being worked on.
I would question if that is true. We have plans that work; using photonic systems instead of electrical signals. However the budget and dedicated focus into researching this has not quite been there just yet. Saying that, there are a few recently young collaborations looking into this more steadily now.
I did my PhD in that area, building the first working superconducting quantum processor (working in the sense of showing quantum speed up, although practically useless of course). That was one of the most fun things I did my entire life, I basically could work on all of the aspects of the computer from the cryostat, the microwave setup, control electronics, PCB manufacturing, chip design and fabrication, soldering, measurement software (written in Python and C++) to doing quantum theory calculations and analysing and visualising data. Nothing I did in my software career ever came close to that level of satisfaction (though there was also a ton of frustration involved).
So yeah I would be happy to work in that area again, though today there aren't that many well paying jobs there yet so I would take a big pay cut if doing that work, but if I wouldn't need to worry about money I would definitely work in that area again.
What a fascinating project you must have had! I've been studying quantum mechanics/computing myself a lot lately. I wonder, if there is anything practical I can try doing at home.
Quantum optics experiments are probably the most accessible for garage hobbyists but it’s still a ~$k hobby once you start buying lasers, electronics and optics.
I remember a very simple experimental setup we did at my initial physics class, my university at the time was in construction (we didn't have equipped labs), with a result similar to the two slit experiment by shining a cheap laser at an angle on a cd/dvd. Something like this: https://www.reddit.com/r/Physics/comments/paqnya/doubleslit_...
I had the same experience, it was very fun, but makes it extremely difficult to get excited for corporate career goals after doing something like that.
The irony here is that if you look at the job postings of quantum hardware vendors, they ask for a laundry list of skills that only a small handful of people on Earth realistically possess (you included).
People are given the impression that there's this outsized demand for Qiskit jockeys, when in reality, what we're currently calling quantum computers are basically physics experiments with the cables cleaned up and hidden in a cabinet. The results you get from these things are tightly coupled to their hardware implementation, and you need people who can work, or at least think, up and down the full stack to get even scientifically useful results. Same goes for quantum sensors, networks, and other so-called adjacent technologies.
If money weren't an object, which labs or lines of research would be the most interesting to you? Do you have strong personal preferences between university/academic research, national labs, and private/startup research roles?
Back to the reality where money is a real factor, what was the difference in compensation like? Was it like a 10x difference or closer to 2x?
I'm asking because I'm a software engineer/founder, but I stepped back from my career due to burnout. I went back to college to study physics and geek out on quantum computing, but I know it'll take grad school (likely a PhD plus postdoc) to grok the full stack. Trying to get a sense of what might be ahead of me.
I have a computer science degree but whenever I start reading about quantum computing I'm lost within minutes. Is there a good way to start studying the basics of quantum computing? I inevitably land on IBM's website, and it always feels like it is pure marketing material.
I'd recommend starting with Quantum Computation and Quantum Information by Isaac Chuang and Michael Nielsen ("Mike and Ike"). It's the text used in most intro courses.
There's an "Intro to Quantum Mechanics" section that covers what's strictly necessary to understand quantum algorithms.
I think the best, and also most popular, textbook for a Quantum Mechanics 1 course is "Introduction to Quantum Mechanics" by David J. Griffiths. This is also what Claude says.
But you also need some math: Complex numbers, linear algebra, some basics of partial differential equations.
But a traditional university course in quantum mechanics aims at doing quantum mechanics in 3-dimensional space, to solve electron orbitals and energy levels of hydrogen atom. But all this 3-dimensional mathematics, you don't necessarily need if you just want to read about quantum computers. Maybe some quantum computers textbook has a presentation of the basics of quantum mechanics that leaves out the topics that traditional physics needs, because traditionally physics was interested in how atoms are build.
> Is there a good way to start studying the basics of quantum computing?
Most quantum mechanics theory out there is taught by physicists.
You'll discover that their brain works in a way that's fundamentally different than that of a computer scientist, making it really hard.
Very specifically, you'll find that they are basically incapable to reason without physical support and/or experiments and sticking to a theoretical presentation of the subject from first principles is not something they can materially do.
Even Scott Aaronson, who claims to try to explay QM and QC using only math falls back to talking about particles and spin and shit after the fourth paragraph.
My recommendation: if you want to learn QM from first mathematical principles, avoid like the plague anything written by a physicist: they're all parroting each other tracing all the way back to Dirac and Bohr.
If you find a book that can talk about QM without using the following words "double slit experiment", "hydrogen atom", "spectrum", "spin", "wave", and only use terms taken from linear algebra in infinite dimensions then you stand a chance to understand.
Not op but I was subjected to a statistical physics exam where the examiner didn't quite appreciate the Kolmogorov axiomatization of the probability theory (which I majored in). It was weird to say the least...
As far as I remember probability distributions were clearly used all over the course but were introduced in a "probability light" manner (which probably made sense for people studying physics but not so much for me).
This is exactly what I remember from every physics course I took in my life: many physicists use math as a blunt tool rarely even bothering explaining them, and almost never justifying why the tool is actually applicable to the problem at hand (e.g. by simply stating that the axioms of the math seem to align with physical observations at all times, thereby very much justifying the use of the mathematical framework).
Far worse, many a physic teacher doesn't even understand the tools they're using from math: they're just parroting and regurgitating from memory a combo of the textbook and what they've been told all the way to grad school, and if you happen to manage to corner them after class to dig a little, you quickly discover how shallow their understanding of the math actually is.
Both Thermodynamics and Electromagnetism were initially hell on earth for me for this very reason: the profs were both incapable of explaining what the tools were and did, how they worked and why they were applicable. All they wanted was for you to absorb and memorize the formulas and stop asking all these stupid questions about the math.
When I finally understood the math tools underlying the two subjects, both thermo and electromagnetism became crystal clear, but boy was the initial exposure an effing headache.
A very good example of this is the famous book "div, grad, curl and all that" that many people hail as excellent. Well, I strongly disagree. It was written by a physicist, and the whole book is laden with references to either fluid mechanics or electromagnetism. It never is capable of explain things without making reference to physics when the tools are in fact completely independent of it.
To the extent that one doesn’t need measure theory to do statistical mechanics there is no need to teach measure theory in a statistical mechanics course.
“If anyone wants to concentrate his attention on infinite sets, measure theory, and mathematical pathology in general, he has every right to do so. And he need not justify this by pointing to useful applications or apologize for the lack of them; as was noted long ago, abstract mathematics is worth knowing for its own sake.
But others in turn have equal rights. If we choose to concentrate on those aspects of mathematics which are useful in real problems and which enable us to carry out the important substantive calculations correctly – but which the mathematical pathologists never get around to – we feel free to do so without apology.”
[Jaynes 2003, p. 673]
By the way, rigour and generality are different things.
> To the extent that one doesn’t need measure theory to do statistical mechanics there is no need to teach measure theory in a statistical mechanics course.
I never assumed otherwise. That being said, I couldn't be bothered to memorize and reproduce the handwavy exposition that made sense to a particular physicist. And it's not that I was there to prove a point - I was asked about the basic constructions like probability distributions, densities etc.
> infinite sets, measure theory, and mathematical pathology
> By the way, rigour and generality are different things.
Measure theory and Kolmogorov axiomatization addressed very real problems like Bertrand's paradox plaguing classical probabilit to the point that it was often seen as a black art rather than science. Moreover, stochastic processes in continuous time are not very intuitive and a sound theory would be next to impossible to develop without solid foundations.
You can’t exactly take the physics out of quantum computing… otherwise you’re just left with linear algebra with a certain set of axioms.
Physics is full of examples of math informed by physical phenomena. There are some good QM/quantum optics books that heavily lean on the linear algebra.
> You can’t exactly take the physics out of quantum computing
Why? I've actually heard even physicists claim the exact opposite.
> otherwise you’re just left with linear algebra with a certain set of axioms.
You say it like it's a bad thing. In my book, it's a very, very good thing.
> Physics is full of examples of math informed by physical phenomena.
Yes indeed, it is. And many a discovery in math actually came from physics in the first place.
And the magic of math is: it extirpates the interesting principles and patterns from the muck of physical reality, making it available, stripped of its lowly origins, to reason with and apply to completely different contexts, including other areas of physics and engineering and CS.
> There are some good QM/quantum optics books that heavily lean on the linear algebra.
Please list some, I'd be very happy to peruse them.
Specifically please list some that don't just "lean" on linear algebra but use it exclusively.
Many a QM book basically expounds on the fact that it is both possible and legitimate to derive QM axiomatically and without ever resorting to physical references, only to immediately do the exact opposite of what they claim in the next chapter.
Computing is the science of constructing abstractions. For quantum computing to be computing, it must be separable from the physics. What you have just said is equivalent to "you can't take the semiconductor physics out of silicon computing."
Many good attempts are being made to do exactly this with QC, and it is a good thing.
When I was asked to work on this stuff (I didn't want to because I knew very little about it, but it was a "do you like eating hot food and sleeping inside" kind of moment) I got this book: https://amzn.eu/d/chnBwVy
I think it provides very useful abstractions for thinking about QC.
To support that last scenario, where the language service, debugger, simulator, even package references, can run entirely in the browser, we built the whole thing using Rust compiled to WebAssembly, and our VS Code extension runs as pure JavaScript and Wasm. If interested you can dig into the implementation at https://github.com/microsoft/qsharp .
You need to understand some mathematics before learning quantum computing. I can recommend 'Essential Mathematics from Quantum Computing' by Leonard S. Woody III, which is short, easy to understand and covers the basics. If you want to go more in-depth into the mathematics involved, then you have 'Linear Algebra and its Applications', by Gilbert Strang, but this book is exclusively about linear algebra, the mathematics that you use with quantum computing, not about quantum computing itself.
There are a couple of popular books about quantum computing in a general sense that could be interesting to read to get an idea about the subject, for example Scott Aaronon's 'Quantum Computing Since Democritus' and Michael A. Nielsen and Isaac L Chuang's 'Quantum Computation an Quantum Information'. I do have the feeling, though, that these will be too deep for a general audience. Interesting and appealing, for sure, but perhaps difficult to understand for most people without a background in the matter.
Some lectures can be really interesting as well, but, again, probably at a level that is not approachable wihout some degree of academic knowledge on the matter. for example, Ronald de Wolf's quantum computing lecture notes from the University of Amsterdam, John Preskill's quantum information lecture notes from the California Institute of Technology, and Scott Aaronson's introduction to quantum science lecture notes. Probably all these lectures are available online.
Probably the best book to learn everything from the maths to the actual physical systems is 'Quantum Computing: From Linear Algebra to Physical Realizaitons', by Mikio Nakahara and Tetsuo Ohmi. This is a really complete book but also... a very expensive book! It's an academic book so not that approachable for the general public, but a great complement for those studying the subject as part of an academic course.
If you want to learn rudiments of how to program with Quiskit, and other topics, vendors like IBM provide excellent resources to get the basic ideas without the need to go too deep. If you want to know more, I would recommend perhaps to do a Masters or something like that. It's not a simple topic, it requires actual study to learn physics, mathematics, and other aspects of the technology.
56 comments
[ 2.5 ms ] story [ 119 ms ] threadwell....ummm...............you see.........we are really happy with the progress we made so far and continue to make more progress.
something like that anyway. Not a single one ever says yeah real soon or defiantly by this date. The people that work there on other things basically laugh and say probably never but its an interesting job. To me Q-day is the same as every research stage tech, somewhere between tomorrow and never.
Disclaimer I never used the term q-day before but am adopting it for ease of commenting.
All of them have some sort of post quantum security program.
None of them have deployed post quantum security at scale.
To me this means that they have a estimate of >10 years <30 years for Q day.
I disagree with them - I think >20 years < 50 years... but wtf do I know! I'm a fella on the internet with an axe to grind :)
Rather an understatement. These are absolutely foundational engineering problems which nobody yet knows how to properly solve.
So yeah I would be happy to work in that area again, though today there aren't that many well paying jobs there yet so I would take a big pay cut if doing that work, but if I wouldn't need to worry about money I would definitely work in that area again.
The irony here is that if you look at the job postings of quantum hardware vendors, they ask for a laundry list of skills that only a small handful of people on Earth realistically possess (you included).
People are given the impression that there's this outsized demand for Qiskit jockeys, when in reality, what we're currently calling quantum computers are basically physics experiments with the cables cleaned up and hidden in a cabinet. The results you get from these things are tightly coupled to their hardware implementation, and you need people who can work, or at least think, up and down the full stack to get even scientifically useful results. Same goes for quantum sensors, networks, and other so-called adjacent technologies.
Back to the reality where money is a real factor, what was the difference in compensation like? Was it like a 10x difference or closer to 2x?
I'm asking because I'm a software engineer/founder, but I stepped back from my career due to burnout. I went back to college to study physics and geek out on quantum computing, but I know it'll take grad school (likely a PhD plus postdoc) to grok the full stack. Trying to get a sense of what might be ahead of me.
Or, asking Claude to tell me about quantum mechanics? </facepalm>
There's an "Intro to Quantum Mechanics" section that covers what's strictly necessary to understand quantum algorithms.
For lectures, John Preskill's lectures from the Quantum Computation course at CalTech: https://youtube.com/playlist?list=PL0ojjrEqIyPy-1RRD8cTD_lF1...
^^ The best resource there is to start with.
--
And a HEALTHY understating of ETYMOLOGY
---
Meaning:
we are realizing the fabric of the reality a we speak it
Speak is an interesting WERD
Understanding druidics and etymology will bring you close.. this is how you fabricate youre reality
But you also need some math: Complex numbers, linear algebra, some basics of partial differential equations.
But a traditional university course in quantum mechanics aims at doing quantum mechanics in 3-dimensional space, to solve electron orbitals and energy levels of hydrogen atom. But all this 3-dimensional mathematics, you don't necessarily need if you just want to read about quantum computers. Maybe some quantum computers textbook has a presentation of the basics of quantum mechanics that leaves out the topics that traditional physics needs, because traditionally physics was interested in how atoms are build.
Most quantum mechanics theory out there is taught by physicists.
You'll discover that their brain works in a way that's fundamentally different than that of a computer scientist, making it really hard.
Very specifically, you'll find that they are basically incapable to reason without physical support and/or experiments and sticking to a theoretical presentation of the subject from first principles is not something they can materially do.
Even Scott Aaronson, who claims to try to explay QM and QC using only math falls back to talking about particles and spin and shit after the fourth paragraph.
My recommendation: if you want to learn QM from first mathematical principles, avoid like the plague anything written by a physicist: they're all parroting each other tracing all the way back to Dirac and Bohr.
If you find a book that can talk about QM without using the following words "double slit experiment", "hydrogen atom", "spectrum", "spin", "wave", and only use terms taken from linear algebra in infinite dimensions then you stand a chance to understand.
Far worse, many a physic teacher doesn't even understand the tools they're using from math: they're just parroting and regurgitating from memory a combo of the textbook and what they've been told all the way to grad school, and if you happen to manage to corner them after class to dig a little, you quickly discover how shallow their understanding of the math actually is.
Both Thermodynamics and Electromagnetism were initially hell on earth for me for this very reason: the profs were both incapable of explaining what the tools were and did, how they worked and why they were applicable. All they wanted was for you to absorb and memorize the formulas and stop asking all these stupid questions about the math.
When I finally understood the math tools underlying the two subjects, both thermo and electromagnetism became crystal clear, but boy was the initial exposure an effing headache.
A very good example of this is the famous book "div, grad, curl and all that" that many people hail as excellent. Well, I strongly disagree. It was written by a physicist, and the whole book is laden with references to either fluid mechanics or electromagnetism. It never is capable of explain things without making reference to physics when the tools are in fact completely independent of it.
“If anyone wants to concentrate his attention on infinite sets, measure theory, and mathematical pathology in general, he has every right to do so. And he need not justify this by pointing to useful applications or apologize for the lack of them; as was noted long ago, abstract mathematics is worth knowing for its own sake.
But others in turn have equal rights. If we choose to concentrate on those aspects of mathematics which are useful in real problems and which enable us to carry out the important substantive calculations correctly – but which the mathematical pathologists never get around to – we feel free to do so without apology.”
[Jaynes 2003, p. 673]
By the way, rigour and generality are different things.
I never assumed otherwise. That being said, I couldn't be bothered to memorize and reproduce the handwavy exposition that made sense to a particular physicist. And it's not that I was there to prove a point - I was asked about the basic constructions like probability distributions, densities etc.
> infinite sets, measure theory, and mathematical pathology > By the way, rigour and generality are different things.
Measure theory and Kolmogorov axiomatization addressed very real problems like Bertrand's paradox plaguing classical probabilit to the point that it was often seen as a black art rather than science. Moreover, stochastic processes in continuous time are not very intuitive and a sound theory would be next to impossible to develop without solid foundations.
They don’t solve the “paradox” - and it can be “solved” without them.
https://bayes.wustl.edu/etj/articles/well.pdf
Physics is full of examples of math informed by physical phenomena. There are some good QM/quantum optics books that heavily lean on the linear algebra.
Why? I've actually heard even physicists claim the exact opposite.
> otherwise you’re just left with linear algebra with a certain set of axioms.
You say it like it's a bad thing. In my book, it's a very, very good thing.
> Physics is full of examples of math informed by physical phenomena.
Yes indeed, it is. And many a discovery in math actually came from physics in the first place.
And the magic of math is: it extirpates the interesting principles and patterns from the muck of physical reality, making it available, stripped of its lowly origins, to reason with and apply to completely different contexts, including other areas of physics and engineering and CS.
> There are some good QM/quantum optics books that heavily lean on the linear algebra.
Please list some, I'd be very happy to peruse them.
Specifically please list some that don't just "lean" on linear algebra but use it exclusively.
Many a QM book basically expounds on the fact that it is both possible and legitimate to derive QM axiomatically and without ever resorting to physical references, only to immediately do the exact opposite of what they claim in the next chapter.
Many good attempts are being made to do exactly this with QC, and it is a good thing.
I think it provides very useful abstractions for thinking about QC.
Now, if you're interested in how quantum computers operate, well good luck. That's a whole other beast.
[1] https://youtu.be/F_Riqjdh2oM
Our VS Code extension is trivial to install (https://learn.microsoft.com/en-us/azure/quantum/install-over...) or just try it entirely in the browser with Visual Studio Code online (https://vscode.dev/quantum/playground/)
To support that last scenario, where the language service, debugger, simulator, even package references, can run entirely in the browser, we built the whole thing using Rust compiled to WebAssembly, and our VS Code extension runs as pure JavaScript and Wasm. If interested you can dig into the implementation at https://github.com/microsoft/qsharp .
Happy to answer any questions!
There are a couple of popular books about quantum computing in a general sense that could be interesting to read to get an idea about the subject, for example Scott Aaronon's 'Quantum Computing Since Democritus' and Michael A. Nielsen and Isaac L Chuang's 'Quantum Computation an Quantum Information'. I do have the feeling, though, that these will be too deep for a general audience. Interesting and appealing, for sure, but perhaps difficult to understand for most people without a background in the matter.
Some lectures can be really interesting as well, but, again, probably at a level that is not approachable wihout some degree of academic knowledge on the matter. for example, Ronald de Wolf's quantum computing lecture notes from the University of Amsterdam, John Preskill's quantum information lecture notes from the California Institute of Technology, and Scott Aaronson's introduction to quantum science lecture notes. Probably all these lectures are available online.
Probably the best book to learn everything from the maths to the actual physical systems is 'Quantum Computing: From Linear Algebra to Physical Realizaitons', by Mikio Nakahara and Tetsuo Ohmi. This is a really complete book but also... a very expensive book! It's an academic book so not that approachable for the general public, but a great complement for those studying the subject as part of an academic course.
If you want to learn rudiments of how to program with Quiskit, and other topics, vendors like IBM provide excellent resources to get the basic ideas without the need to go too deep. If you want to know more, I would recommend perhaps to do a Masters or something like that. It's not a simple topic, it requires actual study to learn physics, mathematics, and other aspects of the technology.