Trump administration establishes $75M quantum computing centers
thehill.com
thehill.com
> bipartisan
Also by coincidence (?) the first time I've seen that word used recently in a context that wasn't preceded by the words lack of or similar.
Or just say Obama wouldn't have the guts to do it[0].
[0]https://www.nydailynews.com/news/national/trump-launched-yem...
If or when it makes sense, they can always increase funding for these three centers and or to build additional centers. Which is exactly what I'd expect in the coming years.
Not surprisingly, the bulk of that was from SoftBank’s Vision Fund: https://asia.nikkei.com/Business/SoftBank2/SoftBank-suffers-...
Your premise is that it'll stop at $75 million in funding. I'd bet against that premise. The US Government has a tendency to start its programs small and expand them considerably over time.
Besides, the US simultaneously has several of the world's largest companies pouring resources into quantum computing (Google, IBM, Microsoft, Amazon, Honeywell, Lockheed, Intel, et al.). It's not as though $75 million is the extent of US investment into the space.
And I mean, look at the last paragraph
> ... the NSF that would be given $100 billion over five years to invest in American research and technology issues, including quantum computing.
Which seems low when you consider that we spent $430 bn on the F35 and lifetime expected cost is 1.5tn for more acquisition and maintenance. Governments work with larger amounts of money and when you look at science (arguably the best way to get ahead in military) it is pennies (CERN was funded internationally and only cost around $20bn over 10 years and $1bn/yr for operation). I mean the largest super computers cost only a couple hundred million, which means if Google or Facebook wanted to, they could compete.
Quantum computing ? I've seen just a few months ago some article about a single start-up raising >200M ?
We know enough about quantum computers to be able to build some of them in limited ways which are commercially useful in very specific domains, so then companies can get investment to do that.
But we still don't really understand all of the fundamentals, and it's always hard to raise investment for fundamental research.
Suppose you could prove that building a quantum computer that can run Shor's Algorithm on interestingly large numbers is impossible. Knowing that would be of immense value. People could stop wasting time trying to create it or defend against it. But how would anybody commercialize that information? Who has the incentive to fund that research?
In which way are quantum computers commercially useful?
VC Bait seems like a natural fit. Just say you are making a quantum computer that predicts global warming trends using blockchain. Might want to buy a wheel barrel for all your money you’ll be leaving that meeting with.
Eh, bipartisan stuff still happens. Look at the military industrial complex. Expanding executive power, expanding the surveillance state. Pro wall street regulation repeal.
Usually its to screw us
However, all research institutions take a cut of grant money in what is usually called "Facilities and Administration" cost. My undergrad rate was 50% of the proposed sum. Obviously the exact rate varies, but the fee remains.
Ex. If a professor is writes a proposal for 1M. When the funding agency awards it they tack on another 1M for the institution.
This is why "expensive" research is favored in universities, over theoretical work. A big part of tenure review is how much money you have brought in in funding, because that's a direct measure of how much money you made the institution.
So 75M is more like 30M-40M of directly funded research, with the rest going to the institutions.
EDIT: Berkeley's F&A goes at high as 60%. https://spo.berkeley.edu/policy/fa.html#rates
At a place like Berkeley, where I did my PhD (but not in anything quantum related), a PhD student and a postdoc both cost a professor something like $75k/year in salary and benefits (money not spent on postdoc salary basically goes to student tuition). Add in the professors salary as well (which is often substantially supported by grants), figure $150k/year for the prof. So in people costs alone, let’s say 1 professor and 2 trainees, that’s about $300k/year, or $1.5M/5 years. Multiply by 30 professors supported, and you’re at $45M, which is 60% of the $75M. And yeah, this is assuming that experiments are free.
Now is 20-30 professors a lot? If sufficiently narrow and esteemed, absolutely. There were 29 people at the 1927 Solvay Conference. Give them an extra couple months where they aren’t sweating a grant, and that’s a lot of time to think.
To quote Major General Smedley Butler: "A racket is best described, I believe, as something that is not what it seems to the majority of the people. Only a small "inside" group knows what it is about. It is conducted for the benefit of the very few, at the expense of the very many. Out of war a few people make huge fortunes."
Higher education is a rachet.
Students pay ever-higher tuition, which at some level is backstopped by the government. If you don't go to college and pursue prestigious degrees the job market will be inaccessible, beyond basic skill entry level.
Graduate students are exploited laborers for the promise of a PhD and a letter of recommendation for a postdoc. Drawing from a global pool of talent for cheap research labor. If you don't do everything your advisor says you will lose your visa, or not get a publication and your academic career is dead-on-arrival.
Professors are in an environment that encourages pursuing expensive application-based research and high impact publications to pad their resumes for tenure. If you don't rake in the money and publish in "prestigious" journal (usually the walled off ones) you will not be considered for tenure, a raise, etc.
Tax dollars fund research institutions that take their generous "administration" fees and then hand over findings to walled garden journals. If you don't fund research we will not make the breakthroughs that gave us out "comfortable" way of life.
In the US, student athletes (until recently) could not profit off their likeness and all the money went to the school.
At the end of the day, the team of MBAs and administrators make fat salaries. This wouldn't be so bad if institutions used the revenue to improve education and dissemination of knowledge. Instead, they build fancy stadiums and raise tuition.
(Still crazy high, of course!)
What are useful metaphors in the application or use of quantum computers?
The problem is pop science crap that tries to explain superposition and entanglement with complete word salad instead of "linear combination" and "product vector cannot be factored into tensor product of single-qbit states", respectively.
Anyway it is extremely doubtful that more programmers will need to learn how to program a quantum computer than, say, will need to learn how to program a GPU. They're both useful co-processors for very specific workloads. Programming will remain a fundamentally classical endeavor.
Taking the analogy of a GPU, how would you describe what a quantum coprocessor could do for a specialist (in, say, neuroscience or material science)? What kind of datasets would be appropriate? How should they think about what can be done with quantum processing? That's where I think there is room for metaphor development.
For materials scientists the value proposition is clear: quantum computers will enable efficient quantum chemistry simulations. Here is an overview paper: https://arxiv.org/abs/1808.10402
Quantum computing (the integer-factoring kind) is the focus of only the UC Berkeley-led consortium. This effort accounts for 1/3 of the announced funding.
The other two centers will work on Quantum networking (UIUC) and Quantum sensing (U Colorado).
Original NSF announcement:
https://www.nsf.gov/news/special_reports/announcements/07212...
Any recommended reading materials on this?
This isn't like the cold war days. The quantum computing research community is close-knit and people would notice researchers being hoovered up by the NSA; this hasn't happened.
Shor's algorithm is undeniably a groundbreaking result but is not the killer app of quantum computers. It's more of an unfortunate side-effect.
[0] https://blog.cloudflare.com/the-tls-post-quantum-experiment/
Yes, but the NSA could still decrypt messages from the past if they recorded and stored them.
How do you develop a curriculum for something that has not been invented yet and might not even be possible to expand to a useful level? How can you have a workforce?
Sounds like someone was just cutting and pasting from a general policy...
Of course if he also succeeds in abolishing universities' non-profit status as he's recently started adding to his culture war talking point reservoir, not even Americans will be there to run this thing.
https://scottlocklin.wordpress.com/2019/01/15/quantum-comput...
Can somebody dispute this claim?
As an experimentalist, I would agree with the sentiment that the potential future applications of Quantum computing probably receive too much media attention, given the maturity level of existing technology.
The technical arguments as to why building a useful QC will be impossible are a bit more shaky.
First, the post seems to imply that the calibration effort scales with the number of gates in the algorithm. This is false. In reality, the number of interactions that need individual calibration is basically the number of qubit-qubit pairs exposed by the gate library. The most mainstream approach to error-corrected QC only uses nearest-neighbor interactions, and hence the scaling is linear.
Second, it is not clear to me why the number of computational basis states (2^N) is relevant to the engineering at all. Following this line of thinking, the recent Quantum supremacy result by Google already amounted to a mastery of 2^53 ~ 10^16 degrees of freedom.
Third, an argument is made that large-scale error correction will not work because of correlated errors, of unspecified nature. I think a claim like this should come with a mention of at least one concrete source of such errors, so that we could estimate its magnitude and potential severity. Note that such calculations are almost the essence of day-to-day work of a physicist.
In the absence of more detail, I can make a generic counterargument: Any phenomenon causing such correlated errors by definition affects multiple physical qubits at once, and will tend to be more macroscopic in nature. This is in contrast with the processes that limit the fidelity of one- and two-qubit operations, which is what the error-correcting code will take care of. Macroscopic disturbances are exactly the ones that we can attempt to shield against with clever engineering.
Google (or anyone else) hasn't shown an implementation of an error correcting code, so we do not have data points for a model-free "ruler extrapolation" of logical error rate vs. lattice size.
In fact, I think the Sycamore qubits were "pre-threshold", i.e. no error correction gain possible even in theory. I wonder if someone will correct/confirm me. I remember the readout fidelity was particularly poor.
Furthermore, I would argue that the large readout errors make the observed scaling of total error slightly less impactful.
But don't get me wrong, it's still a monumental achievement.
OK, here are $x Billion, make us #1 in this field.
Quantum technology is more than just computers.
Anyone know of any good quantum tech based companies in Boulder?
There's no "agenda" at work here, you're just being needlessly paranoid.
It was a White House initiative, so the headline seems to be accurate.