5 ms·

Quantum Computation Lecture Notes (2022)

166 points by ibobev 1y ago

revskill 1y ago
How can a person become so good at researching ?
- lightbendover 1y ago
  (1) be naturally gifted, (2) avoid falling down wells of distraction, (3) be lucky. Don’t sleep on (3), it’s easy to call it capitalizing on opportunity in hindsight when it was honestly just luck.
  - TechDebtDevin 1y ago
    luck in terms of natural intelligence and focus. But generally people can approve their ability to avoid falling down the "wells of distraction". This year I set time filters for apps on my phone and its made a stark difference. Even though I can turn off "work mode" to get around it, that little reminder has saved me hundreds of hours as I usually just put down the phone when I see it.
  - jasonhong 1y ago
    I'd also add (4) be incredibly curious about lots of things; (5) surround yourself with other smart, curious, and committed people who have a culture of critiquing ideas; and (6) devote a lot of time to deep thinking.
    - rwoerz 1y ago
      (8) be good in counting things, (h) be consistent in your thinking, (10) have a good memory, (11) be good in counting things, (12) refrain from making silly comments
- xeonmc 1y ago
  just get nerd-sniped.
- gaze 1y ago
  I don't know how else to say it but you just have to do it. It's like asking how to get good at running. You run.
- graycat 1y ago
  > How can a person become so good at researching ? My time in my Ph.D. program and some of the work in my career (getting paid) suggest that I was "good at researching". But I left such research due to wanting to get paid more, and settled on starting a business, owning it, and making it valuable. If some research can help the business, fine, but the real goal is just the money from a successful business. On (academic) research, one lesson no one ever mentioned to me but eventually I formulated: Pick a field of research. Then in that field a lot about what is expected, respected, intended, valued or not, ..., is not much spoken about and not made clear -- clear that have fertile ground for politics. Then, for such questions, the answers you guess or get in some one field will likely be quite different in another. In some fields can get reminded of the old quip: "Haydn wrote 101 symphonies or one symphony 101 times?" Or at times can believe that with high probability, a paper gets read by just two people, the peer reviewer and the author; as a result of that case, the only accomplishment of papers, good or bad, are that they get counted as in someone with 50 papers is regarded as better than someone with only 4. Ah, tough to prove that the paper will never get 1000 readers! For research, one approach is to study a (assume an academic) field, crawl down some narrow alley or rabbit whole, see a question with no answer, consider the broad status of the field, then if making progress on the question seems not obviously impossible, give it a try. By a few days or weeks should have an answer, a partial answer, or hints that by continuing you might get something. Another approach is to pick a problem mostly on your own and not from, trying to extend, published research. You might follow some instance of personal curiosity or something from some other field, e.g., do some math, optimization, statistics, ... research from problems in the environment (why the ups and downs of lobsters in east Canada?), medical testing, the supply chain, some engineering problem, some business problem, etc. Do note that in the US, after radar, the proximity fuze, submarine acoustics, code breaking, jet engines, the "bomb", the US military had plenty of both money and problems, and that funded a lot of US research. Now there seems to be a general view: We don't know what research directions will yield powerful results, but since we can't afford to miss out on some big results or fall behind, we will continue to fund research. Non-military research seems less eager for results and to have less money. Ah, be good at the politics, e.g., even follow "Always look for the hidden agenda." If working in an organization, beware of "goal subordination", i.e., others working to have you fail.
polamolo 1y ago
I feel like I've seen/done this before. Could I be stuck in a groundhog day?
- zara_is_reading 1y ago
  I’ve 70.71% seen it before and 70.71% not seen it before.
rvz 1y ago
Well right now I am very skeptical, but I think we have somewhat given quantum computing plenty of time (we have given it decades) unless someone can convince me that it is not a scam. Right now it hasn't amounted to anything useful, other than Shor's and 'experiments' and promises and applications that are no better done on a GPU rack right now.
- adastra22 1y ago
  Tab is the equivalent of “there will be worldwide demand for 4-6 computers.”
- dandanua 1y ago
  Who are "we"? And why those "we" think that a branch of fundamental science that have people involved all around the globe could be a scam? It's nowhere close to the cryto mania, where there is only one end goal.
- n4r9 1y ago
  For quantum computing, as a rule of thumb I generally look to what Scott Aaronson says. And as you suggest, while some cool stuff is being done both in industry and academia, we are nowhere near general quantum computers. I haven't checked what his outlook is for the next 5-10 years.
  - honzaik 1y ago
    this may give you an idea about his current outlook https://www.youtube.com/watch?v=DQFyQgA_GE4 https://www.youtube.com/watch?v=DQFyQgA_GE4
- bradly 1y ago
  Not quantum computation, but quantum mechanics are being used in QKD satellites today to hedge against RSA being broken. Pretty neat.
  - bawolff 1y ago
    Quantum computers is not a scam, but QKD basically is. There is no scenario where QKD actually makes practical sense.
m3kw9 1y ago
As soon as a math equation comes up I get lost.
ofjcihen 1y ago
Thanks for this. I’ve recently become very interested in QC and purchased and read Quantum Computation and quantum Information which I think is the standard book on the subject right now. I’m even more interested in applying what I’ve learned but I’m at a loss as to how to begin working in the industry. Aside from getting a new masters degree I wouldn’t know where to begin and resources on the matter are understandably sparse.
- abdullahkhalids 1y ago
  You can definitely work at QC companies even without having a degree in the field. Many QC companies hire people from other fields because they require that expertise, say people with experience in numerical optimization. Of course, many QC companies also hire software engineers because they have complex internal software. If you are a software engineer, you can start there and then start to move laterally within the company. Source: work at a QC company as a scientist.
  - ofjcihen 1y ago
    That’s something I didn’t think about. Thank you
- dheera 1y ago
  It's actually not that difficult to pick up quantum mechanics and quantum computing if you have a solid foundation in linear algebra. QC really just reduces down to "applied linear algebra on crack". If you're in AI, you might be pleased to know that the probability distribution of a particle in its various energy states is related to the softmax of the negative values of those energies times temperature, which is where the concept of LLM "temperature" comes from. If you have linear algebra background, those energies are the eigenvalues of a Hamiltonian. Physics is actually quite beautiful. Getting into industries is another issue though, it seems every company favors credentials over learning ability these days. If you haven't published 1500 papers on the subject you're automatically rejected.
- qnleigh 1y ago
  Yes that's still a great book, though it's starting to get a bit outdated. Some recent developments that would belong in an updated edition: - The section on error correction is still gold, but it doesn't cover "scalable codes" like the Surface Code (and other LDPC codes; lots of exciting progress there) - Superconducting Qubits: https://arxiv.org/abs/1904.06560 https://arxiv.org/abs/1904.06560. - Rydberg Atoms: see Nature Papers from Misha Lukin's group on the subject - Photonic quanum computing These might be hard to follow now, but if you make it through a good chunk of Nielsen and Chuang, then they might become quite readable. Make sure you solve lots of problems or it won't stick. Like other commenters have pointed out, quantum computing companies need lots of software engineers, so that's a very viable entry into the field for many people. Here's an arbitrary list of some relevant skills: - Qutip! You can learn sooo much quantum mechanics by playing around in Qutip, and it's quite easy to use. - Rust or C++ (depending on the company?) - FPGA programming - Python (ofc) - Linear algebra - ...
fogof 1y ago
Very funny to me that lecture 21 is one of the only lecture titles that doesn't reference the name of the originator.
hedgehog0 1y ago
De Wolf's note is also one of the standards right now, and more up-to-date than the QC&QI book: https://arxiv.org/abs/1907.09415 https://arxiv.org/abs/1907.09415
mikestorrent 1y ago
Of course, no discussion of quantum annealing, the only practical form of quantum computation that is likely to exist at scale in our lifetimes.
- adastra22 1y ago
  That's a strong statement. Regardless, the content of the course is explicitly targeted at gate-based quantum computing.
- msgodel 1y ago
  Is it practical? The little I've messed with it it seemed borderline useless. All it can do is QUBO and encoding the problem into the machine topology itself is another QUBO problem that has to be done on a classical computer. People also keep talking about using it for AI but all you can train with it are Boltzmann machines because those are all that map into QUBO problems.
husky8 1y ago
I made a podcast in NotebookLM once I saw equations. Enjoy https://notebooklm.google.com/notebook/bc7616c4-1c71-4a04-b275-0e6cb0141e40/audio https://notebooklm.google.com/notebook/bc7616c4-1c71-4a04-b2...
- vismit2000 1y ago
  Getting this message - "Oops! This audio could not be loaded."

166 points by ibobev 1y ago

revskill 1y ago

How can a person become so good at researching ?

lightbendover 1y ago
(1) be naturally gifted, (2) avoid falling down wells of distraction, (3) be lucky. Don’t sleep on (3), it’s easy to call it capitalizing on opportunity in hindsight when it was honestly just luck.
- TechDebtDevin 1y ago
  luck in terms of natural intelligence and focus. But generally people can approve their ability to avoid falling down the "wells of distraction". This year I set time filters for apps on my phone and its made a stark difference. Even though I can turn off "work mode" to get around it, that little reminder has saved me hundreds of hours as I usually just put down the phone when I see it.
- jasonhong 1y ago
  I'd also add (4) be incredibly curious about lots of things; (5) surround yourself with other smart, curious, and committed people who have a culture of critiquing ideas; and (6) devote a lot of time to deep thinking.
  - rwoerz 1y ago
    (8) be good in counting things, (h) be consistent in your thinking, (10) have a good memory, (11) be good in counting things, (12) refrain from making silly comments
xeonmc 1y ago
just get nerd-sniped.
gaze 1y ago
I don't know how else to say it but you just have to do it. It's like asking how to get good at running. You run.
graycat 1y ago
> How can a person become so good at researching ? My time in my Ph.D. program and some of the work in my career (getting paid) suggest that I was "good at researching". But I left such research due to wanting to get paid more, and settled on starting a business, owning it, and making it valuable. If some research can help the business, fine, but the real goal is just the money from a successful business. On (academic) research, one lesson no one ever mentioned to me but eventually I formulated: Pick a field of research. Then in that field a lot about what is expected, respected, intended, valued or not, ..., is not much spoken about and not made clear -- clear that have fertile ground for politics. Then, for such questions, the answers you guess or get in some one field will likely be quite different in another. In some fields can get reminded of the old quip: "Haydn wrote 101 symphonies or one symphony 101 times?" Or at times can believe that with high probability, a paper gets read by just two people, the peer reviewer and the author; as a result of that case, the only accomplishment of papers, good or bad, are that they get counted as in someone with 50 papers is regarded as better than someone with only 4. Ah, tough to prove that the paper will never get 1000 readers! For research, one approach is to study a (assume an academic) field, crawl down some narrow alley or rabbit whole, see a question with no answer, consider the broad status of the field, then if making progress on the question seems not obviously impossible, give it a try. By a few days or weeks should have an answer, a partial answer, or hints that by continuing you might get something. Another approach is to pick a problem mostly on your own and not from, trying to extend, published research. You might follow some instance of personal curiosity or something from some other field, e.g., do some math, optimization, statistics, ... research from problems in the environment (why the ups and downs of lobsters in east Canada?), medical testing, the supply chain, some engineering problem, some business problem, etc. Do note that in the US, after radar, the proximity fuze, submarine acoustics, code breaking, jet engines, the "bomb", the US military had plenty of both money and problems, and that funded a lot of US research. Now there seems to be a general view: We don't know what research directions will yield powerful results, but since we can't afford to miss out on some big results or fall behind, we will continue to fund research. Non-military research seems less eager for results and to have less money. Ah, be good at the politics, e.g., even follow "Always look for the hidden agenda." If working in an organization, beware of "goal subordination", i.e., others working to have you fail.

polamolo 1y ago

I feel like I've seen/done this before. Could I be stuck in a groundhog day?

zara_is_reading 1y ago
I’ve 70.71% seen it before and 70.71% not seen it before.

rvz 1y ago

Well right now I am very skeptical, but I think we have somewhat given quantum computing plenty of time (we have given it decades) unless someone can convince me that it is not a scam. Right now it hasn't amounted to anything useful, other than Shor's and 'experiments' and promises and applications that are no better done on a GPU rack right now.

adastra22 1y ago
Tab is the equivalent of “there will be worldwide demand for 4-6 computers.”
dandanua 1y ago
Who are "we"? And why those "we" think that a branch of fundamental science that have people involved all around the globe could be a scam? It's nowhere close to the cryto mania, where there is only one end goal.
n4r9 1y ago
For quantum computing, as a rule of thumb I generally look to what Scott Aaronson says. And as you suggest, while some cool stuff is being done both in industry and academia, we are nowhere near general quantum computers. I haven't checked what his outlook is for the next 5-10 years.
- honzaik 1y ago
  this may give you an idea about his current outlook https://www.youtube.com/watch?v=DQFyQgA_GE4 https://www.youtube.com/watch?v=DQFyQgA_GE4
bradly 1y ago
Not quantum computation, but quantum mechanics are being used in QKD satellites today to hedge against RSA being broken. Pretty neat.
- bawolff 1y ago
  Quantum computers is not a scam, but QKD basically is. There is no scenario where QKD actually makes practical sense.

m3kw9 1y ago

As soon as a math equation comes up I get lost.

ofjcihen 1y ago

Thanks for this. I’ve recently become very interested in QC and purchased and read Quantum Computation and quantum Information which I think is the standard book on the subject right now. I’m even more interested in applying what I’ve learned but I’m at a loss as to how to begin working in the industry. Aside from getting a new masters degree I wouldn’t know where to begin and resources on the matter are understandably sparse.

abdullahkhalids 1y ago
You can definitely work at QC companies even without having a degree in the field. Many QC companies hire people from other fields because they require that expertise, say people with experience in numerical optimization. Of course, many QC companies also hire software engineers because they have complex internal software. If you are a software engineer, you can start there and then start to move laterally within the company. Source: work at a QC company as a scientist.
- ofjcihen 1y ago
  That’s something I didn’t think about. Thank you
dheera 1y ago
It's actually not that difficult to pick up quantum mechanics and quantum computing if you have a solid foundation in linear algebra. QC really just reduces down to "applied linear algebra on crack". If you're in AI, you might be pleased to know that the probability distribution of a particle in its various energy states is related to the softmax of the negative values of those energies times temperature, which is where the concept of LLM "temperature" comes from. If you have linear algebra background, those energies are the eigenvalues of a Hamiltonian. Physics is actually quite beautiful. Getting into industries is another issue though, it seems every company favors credentials over learning ability these days. If you haven't published 1500 papers on the subject you're automatically rejected.
qnleigh 1y ago
Yes that's still a great book, though it's starting to get a bit outdated. Some recent developments that would belong in an updated edition: - The section on error correction is still gold, but it doesn't cover "scalable codes" like the Surface Code (and other LDPC codes; lots of exciting progress there) - Superconducting Qubits: https://arxiv.org/abs/1904.06560 https://arxiv.org/abs/1904.06560. - Rydberg Atoms: see Nature Papers from Misha Lukin's group on the subject - Photonic quanum computing These might be hard to follow now, but if you make it through a good chunk of Nielsen and Chuang, then they might become quite readable. Make sure you solve lots of problems or it won't stick. Like other commenters have pointed out, quantum computing companies need lots of software engineers, so that's a very viable entry into the field for many people. Here's an arbitrary list of some relevant skills: - Qutip! You can learn sooo much quantum mechanics by playing around in Qutip, and it's quite easy to use. - Rust or C++ (depending on the company?) - FPGA programming - Python (ofc) - Linear algebra - ...

fogof 1y ago

Very funny to me that lecture 21 is one of the only lecture titles that doesn't reference the name of the originator.

hedgehog0 1y ago

De Wolf's note is also one of the standards right now, and more up-to-date than the QC&QI book: https://arxiv.org/abs/1907.09415 https://arxiv.org/abs/1907.09415

mikestorrent 1y ago

Of course, no discussion of quantum annealing, the only practical form of quantum computation that is likely to exist at scale in our lifetimes.

adastra22 1y ago
That's a strong statement. Regardless, the content of the course is explicitly targeted at gate-based quantum computing.
msgodel 1y ago
Is it practical? The little I've messed with it it seemed borderline useless. All it can do is QUBO and encoding the problem into the machine topology itself is another QUBO problem that has to be done on a classical computer. People also keep talking about using it for AI but all you can train with it are Boltzmann machines because those are all that map into QUBO problems.

husky8 1y ago

I made a podcast in NotebookLM once I saw equations. Enjoy https://notebooklm.google.com/notebook/bc7616c4-1c71-4a04-b275-0e6cb0141e40/audio https://notebooklm.google.com/notebook/bc7616c4-1c71-4a04-b2...

vismit2000 1y ago
Getting this message - "Oops! This audio could not be loaded."