8 ms·

New silicon structure opens the gate to quantum computers

147 points by lainon 9y ago

xt00 9y ago
Anybody who can read the actual PDF -- is this at room temp and no large magnetic field? Those two things seem to be the big stumbling blocks for these types of quantum computers..
- uncoder0 9y ago
  Paper is linked below and way out of my depth but the only mention of temperature I could find was 150 mK so I'd assume this is not done at room temperature.
- milesokeefe 9y ago
  Yep, still a major issue. This was run at 0.15 kelvin (-273c/-459.4f) and they'd like to get it colder: In these experiments, the electron temperature accounts for 10% of the reduction in our visibility, and spin relaxation accounts for the remaining 5-10%. In our experiment we readout the qubits sequentially, reading the left qubit first. Relaxation of the right qubit during the readout of the left qubit is what leads to the asymmetry of the expected visibilities. Relaxation contributions to the readout fidelity can be mitigated by using a faster readout technique such as RF reflectometry or by incorporating a cold amplifier into the readout circuit (9, 10). Further improvements can be made by reducing the electron temperature or using cavity-based measurement approaches (11).
rgbrenner 9y ago
the paper: https://arxiv.org/ftp/arxiv/papers/1708/1708.03530.pdf https://arxiv.org/ftp/arxiv/papers/1708/1708.03530.pdf
- mastazi 9y ago
  Thank you so much, I wasn't aware that the pre-print was on Arxiv. PS the web abstract link (as opposed to the pdf link above) is https://arxiv.org/abs/1708.03530 https://arxiv.org/abs/1708.03530
chunky1994 9y ago
I haven't touched this stuff in a while so take this with a grain of salt. This is good progress since it's about an order of magnitude faster for operations than previously constructed CNOT gates, however it still has many caveats for a semiconducter-like leap towards real quantum computers: a) Low temperature bound for the level of fidelity they want b) Doesn't allow us to engineer quantum chips of more qubits efficiently since the decoherence between quantum dots is still a major issue. c) The science journalism title is a bit misleading. While this happens in a silicon structure there is nothing new about it, what's new is that they managed to use the driving resonance to control the dephasing during the gate operation.
jessriedel 9y ago
FYI: This is for a very different substrate (quantum dots, which are basically individual electrons trapped in special silicon defects) compared to the substrates that have seen more attention for quantum computing (superconducting circuits and trapped ions). They are behind in terms of raw qubit counts -- which are not that meaningful -- and in terms of their overall abilities, but they hope to catch up by building higher quality components that cross the fault-tolerant threshold first. If, like me, you don't already know a lot about quantum computing experiments, this article shouldn't interest you. At best, this is a small step of many thousands that will be taken on the way building a working computer.
ohiovr 9y ago
I know nothing about this stuff but this caught my eye: “The challenge is that it’s very difficult to build artificial structures small enough to trap and control single electrons without destroying their long storage times,” said David Zajac, a graduate student in physics at Princeton and first-author on the study. “This is the first demonstration of entanglement between two electron spins in silicon, a material known for providing one of the cleanest environments for electron spin states.” Electrides like Calcium Aluminate Electride can readily trap individual electrons. And it is stable at room temperatures.
propter_hoc 9y ago
I did graduate research in an area of experimental physics that was quite close to state of the art quantum computing research. It was very exciting, but all the research was pretty much in extreme conditions that aren't really usable for a realistic computing device (ultra-high vacuum, nanokelvin temperatures, high magnetic fields or laser trap confinement, etc.). From the looks of it this paper is in the same vein. Good progress, but the gate isn't quite "open" yet.
- uncoder0 9y ago
  The vacuum, temperature and confinement requirements would seem to be huge problems relative to the exotic material requirement of current gates (Not to diminish the significance of accomplishing this in silicon). As far as I know these 'hard' problems have remained pretty constant in quantum computing. Are we making progress on any of them? Basically, in your opinion how are things progressing in the field with respect to the big problems with making quantum computing mainframe ubiquitous?
- badspeler 9y ago
  That's true but once Science conquers something, engineering isn't very far behind. The apparatus to build Bose-Einstein Condensates was a fucking monster of vacuums and quantum optics but now we can fit a Bose-Einstein Condensate on a microchip. https://arxiv.org/abs/0912.0553 https://arxiv.org/abs/0912.0553
  - techdragon 9y ago
    I Just read that paper and while It’s hardly just a microchip it’s damn impressive considering the technology involved and the requirements it’s fulfilling. It’s amazing that we can now build devices that can produce ultra high vacuums smaller than a hotel minibar, and design systems that are capable of active cooling down to <1K without the use of any cryogenic refrigeration at all.
tim-- 9y ago
My biggest pet peeve about quantum computing is that no one can answer me the question of "what can quantum computing do for me?". The answer I hear is that it helps solve the traveling salesman in record time, and that's all great and everything, but how will quantum computing be able to do things such as decrease the time it takes to train a RNN, or look up data in a database?
- empath75 9y ago
  https://www.nature.com/articles/npjqi201523 https://www.nature.com/articles/npjqi201523 Here are a bunch of potential applications.
- NhanH 9y ago
  Quantum annealing can be used for optimization of functions. Shor’s algorithm of integer factorization would solve (and cause) a whole host of problems for us. But in general, quantum computer is not strictly a superset of improvement over Turing machine. It’s just different. And while it might reduces your database query time, unless you are already working at that abstraction it might probably be invisible changes for you.
  - TrinaryWorksToo 9y ago
    From what I gathered, it's similar to how a CPU and GPU compare: different complexity classes, different problems it's efficient on.
    - asddkk 9y ago
      The CPU-GPU analogy is very good for all sorts of reasons. For some things there's no speedup, for some important things there's a huge speedup, for other things there's some significant speedup, but not game-changing. I tend to think of applications where you might want to brute-force search or simulate over some large set as being where quantum computing will be most significant, but I say that very vaguely and timidly. This gives a number of applications and algorithms; I found some of the references in it really interesting to read: http://math.nist.gov/quantum/zoo/ http://math.nist.gov/quantum/zoo/

147 points by lainon 9y ago

xt00 9y ago

Anybody who can read the actual PDF -- is this at room temp and no large magnetic field? Those two things seem to be the big stumbling blocks for these types of quantum computers..

uncoder0 9y ago
Paper is linked below and way out of my depth but the only mention of temperature I could find was 150 mK so I'd assume this is not done at room temperature.
milesokeefe 9y ago
Yep, still a major issue. This was run at 0.15 kelvin (-273c/-459.4f) and they'd like to get it colder: In these experiments, the electron temperature accounts for 10% of the reduction in our visibility, and spin relaxation accounts for the remaining 5-10%. In our experiment we readout the qubits sequentially, reading the left qubit first. Relaxation of the right qubit during the readout of the left qubit is what leads to the asymmetry of the expected visibilities. Relaxation contributions to the readout fidelity can be mitigated by using a faster readout technique such as RF reflectometry or by incorporating a cold amplifier into the readout circuit (9, 10). Further improvements can be made by reducing the electron temperature or using cavity-based measurement approaches (11).

rgbrenner 9y ago

the paper: https://arxiv.org/ftp/arxiv/papers/1708/1708.03530.pdf https://arxiv.org/ftp/arxiv/papers/1708/1708.03530.pdf

mastazi 9y ago
Thank you so much, I wasn't aware that the pre-print was on Arxiv. PS the web abstract link (as opposed to the pdf link above) is https://arxiv.org/abs/1708.03530 https://arxiv.org/abs/1708.03530

chunky1994 9y ago

I haven't touched this stuff in a while so take this with a grain of salt. This is good progress since it's about an order of magnitude faster for operations than previously constructed CNOT gates, however it still has many caveats for a semiconducter-like leap towards real quantum computers: a) Low temperature bound for the level of fidelity they want b) Doesn't allow us to engineer quantum chips of more qubits efficiently since the decoherence between quantum dots is still a major issue. c) The science journalism title is a bit misleading. While this happens in a silicon structure there is nothing new about it, what's new is that they managed to use the driving resonance to control the dephasing during the gate operation.

jessriedel 9y ago

FYI: This is for a very different substrate (quantum dots, which are basically individual electrons trapped in special silicon defects) compared to the substrates that have seen more attention for quantum computing (superconducting circuits and trapped ions). They are behind in terms of raw qubit counts -- which are not that meaningful -- and in terms of their overall abilities, but they hope to catch up by building higher quality components that cross the fault-tolerant threshold first. If, like me, you don't already know a lot about quantum computing experiments, this article shouldn't interest you. At best, this is a small step of many thousands that will be taken on the way building a working computer.

ohiovr 9y ago

I know nothing about this stuff but this caught my eye: “The challenge is that it’s very difficult to build artificial structures small enough to trap and control single electrons without destroying their long storage times,” said David Zajac, a graduate student in physics at Princeton and first-author on the study. “This is the first demonstration of entanglement between two electron spins in silicon, a material known for providing one of the cleanest environments for electron spin states.” Electrides like Calcium Aluminate Electride can readily trap individual electrons. And it is stable at room temperatures.

propter_hoc 9y ago

I did graduate research in an area of experimental physics that was quite close to state of the art quantum computing research. It was very exciting, but all the research was pretty much in extreme conditions that aren't really usable for a realistic computing device (ultra-high vacuum, nanokelvin temperatures, high magnetic fields or laser trap confinement, etc.). From the looks of it this paper is in the same vein. Good progress, but the gate isn't quite "open" yet.

uncoder0 9y ago
The vacuum, temperature and confinement requirements would seem to be huge problems relative to the exotic material requirement of current gates (Not to diminish the significance of accomplishing this in silicon). As far as I know these 'hard' problems have remained pretty constant in quantum computing. Are we making progress on any of them? Basically, in your opinion how are things progressing in the field with respect to the big problems with making quantum computing mainframe ubiquitous?
badspeler 9y ago
That's true but once Science conquers something, engineering isn't very far behind. The apparatus to build Bose-Einstein Condensates was a fucking monster of vacuums and quantum optics but now we can fit a Bose-Einstein Condensate on a microchip. https://arxiv.org/abs/0912.0553 https://arxiv.org/abs/0912.0553
- techdragon 9y ago
  I Just read that paper and while It’s hardly just a microchip it’s damn impressive considering the technology involved and the requirements it’s fulfilling. It’s amazing that we can now build devices that can produce ultra high vacuums smaller than a hotel minibar, and design systems that are capable of active cooling down to <1K without the use of any cryogenic refrigeration at all.

tim-- 9y ago

My biggest pet peeve about quantum computing is that no one can answer me the question of "what can quantum computing do for me?". The answer I hear is that it helps solve the traveling salesman in record time, and that's all great and everything, but how will quantum computing be able to do things such as decrease the time it takes to train a RNN, or look up data in a database?

empath75 9y ago
https://www.nature.com/articles/npjqi201523 https://www.nature.com/articles/npjqi201523 Here are a bunch of potential applications.
NhanH 9y ago
Quantum annealing can be used for optimization of functions. Shor’s algorithm of integer factorization would solve (and cause) a whole host of problems for us. But in general, quantum computer is not strictly a superset of improvement over Turing machine. It’s just different. And while it might reduces your database query time, unless you are already working at that abstraction it might probably be invisible changes for you.
- TrinaryWorksToo 9y ago
  From what I gathered, it's similar to how a CPU and GPU compare: different complexity classes, different problems it's efficient on.
  - asddkk 9y ago
    The CPU-GPU analogy is very good for all sorts of reasons. For some things there's no speedup, for some important things there's a huge speedup, for other things there's some significant speedup, but not game-changing. I tend to think of applications where you might want to brute-force search or simulate over some large set as being where quantum computing will be most significant, but I say that very vaguely and timidly. This gives a number of applications and algorithms; I found some of the references in it really interesting to read: http://math.nist.gov/quantum/zoo/ http://math.nist.gov/quantum/zoo/