Existing superconducting quantum computers need to be cooled near absolute zero.  For example, some of D-Wave's machines are cooled to about $20 \ \mathrm {mK}$.  Their design uses a dilution refrigerator.  Are there any other cooling methods for superconducting quantum computers besides dilution refrigerators which are capable of achieving such low temperatures?  Are there any specific commercial quantum computer designs or research projects using these other cooling methods?
121982
Is a dilution refrigerator the only way to cool superconducting qubits down to 10 millikelvin? If not, what other methods are there, and why is dilution refrigeration the primary method?
29381
Reading  entertaining piece of a QC enthusiast mining bitcoins with a Quantum Computer (although efficiently mining bitcoins with the current state of QCs is far-fetched, it is quite possible to be done in the next few years), I wonder how exactly will technologies already using Blockchain adapt to the change?  Are they currently being worked upon? How would post-quantum cryptography integrate with existing tech secured using today's cryptography algorithms?
33974
The intuition I have for why quantum computing can perform better than classical computing is that the wavelike nature of wavefunctions allow you to interfere multiple states of information with a single operation, which theoretically could allow for exponential speedup.   But if it really is just constructive interference of complicated states, why not just perform this interference with classical waves?  And on that matter, if the figure-of-merit is simply how few steps something can be calculated in, why not start with a complicated dynamical system that has the desired computation embedded in it. (ie, why not just create "analog simulators" for specific problems?)
6710
Quantum computers are known to be able to crack  a broad range of cryptographic algorithms which were previously thought to be solvable only by resources increasing exponentially with the bit size of the key. An example for that is .  But, as far I know, not all problems fall into this category. On , we can read     Researchers have developed a computer algorithm that doesn’t solve problems but instead creates them for the purpose of evaluating quantum computers.   Can we still expect a new cryptographic algorithm which will be hard to crack using even a quantum computer? For clarity: the question refers to specifically to the design of new algorithms.
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With the advancement of technology in quantum computing, it's becoming more evident that we need to start thinking about protecting the future integrity of our cryptographic standards.  What can we do on binary computers to prevent attacks on cryptographic related items such as password hashes, private keys, and asymmetric key exchange?
29363
I've noticed that Q# favors Little Endian. Meaning that most operations are designed for this type of encoding.  Is is it the same with Qiskit?
97030
If I had a light "diode" - an object that only allowed light (at least for a range of frequencies) to travel through it in one direction, would this necessarily allow violations of the 2nd Law of Thermodynamics?  Or would it be possible to restrict other properties of the device such that it could be okay.  Why I think it should violate 2nd law:   I can place such devices at temperature T in a bath of thermal radiation at temperature T, such that it forms a box which only lets the light in or out.  This would appear to always allow one to create a thermal gradient.  Once a thermal gradient is formed, useful energy can be extracted.  This seems to allow useful energy to always be extracted from a thermal bath and thus give perpetual motion. Release one such device at temperature T in a bath of thermal radiation at temperature T.  Since the photons are absorbed or reflected in one direction, and undisturbed in the other, the device will start moving.  It can use a thermal bath to directly generate useful motion.   Why I think I'm missing something and such a device could potentially co-exist with the 2nd Law:   The above arguments seem valid if the diode was only 'partially' rectifying as well.  However there exist sunglasses which largely reflect on one side, but not from the other side. Researchers have succeeded in using meta-materials to create a "blackhole" for microwaves.   Can anyone help sort this out?
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Is all digital sensor noise thermal?  And what is the relationship between temperature and noise?  For example, as we cooled a CMOS towards absolute zero, would we discover that high-ISO images would be less noisy?  Would they converge towards a truly noiseless image at maximum ISO and absolute zero?
87894
I'm planning on building a system for high CPU and memory performance.  Graphics performance is not a major concern, as I do not plan to use it for gaming.  I noticed that liquid cooling seems to have become common since my last build, and I am wondering if it is needed in my case.  I do not plan to overclock any of the components.  The intended use for the system is primarily development and occasional compute-intensive tasks that will run on all cores continuously for several days to a week.  The system will not normally be in continuous usage like this, but it needs to be capable of occasional extended periods of continuous use at full capacity.  I have included the main components below.  CPU: i7-5960X  Memory: 64GB DDR4  Graphics card: Nvidia GeForce GT 730 2GB  Drive 1: 1TB SSD  Drive 2: 4TB 7200RPM HDD  Power supply: 700W  Is liquid cooling needed for the above build?  If not, is there any advantage in using it?  I have read reviews that mentioned liquid cooling unit failures that resulted in leaks, so I would rather not use it if it is not necessary.  Thanks!
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As we make inroads into Machine Learning, there seem to be plenty of respectable courses available online via Coursera, edX, etc. on the topic. As quantum computing is still in its infancy, not to mention, incredibly daunting, it is vital that easy to understand, introductory courses are made available.  I was able to find these courses:      However, I am not certain how relevant the second course might be.  Obviously, this question may benefit from receiving answers in the near future as the topic steadily becomes mainstream.
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I have a server room about 12 feet square with an unfinished ceiling (exposed ducts and wiring).  It houses a few servers (about ten, 1U and 2U) and some networking gear (four 1U switches, three routers, three modems, two cable boxes).  With the door closed, it runs around 80 degrees Fahrenheit with half the servers turned on.  When I turned on all the servers it reached 86 before I chickened out and propped the door open.  The room is adjacent to air-conditioned office space, but does not itself have dedicated air conditioning.  The ventilation for this room seems to be limited to one duct coming in at ceiling level, with a powered fan to draw air in, and one duct at ceiling level to allow air to flow out (it seems like it may just go into the drop ceiling cavity in the adjacent room).  The adjacent office space stays fairly cool, but I'd prefer not to leave the door propped open all the time.  There is both 110v and 208v service in the room, and plenty of power available.  But there are no windows, and no floor drains (in a pinch we might be able to run a condensation hose through a small hole we'd drill in the wall to a nearby sink area, but only if absolutely necessary).  I've considered portable A/C units, but I'm not sure on sizing and a lot less sure how we would run the exhaust hose(s).  I suppose we could point one at the existing room exhaust duct (air return), but substantially modifying the duct is probably a no-no.  I've also considered installing a fan box in the door of the room, but I'm concerned that this will only drop the temperature a little.  Even right now, with all the equipment on, the room is at 83 degrees with the door open.  And the main building A/C turns off daily at 6 PM to conserve energy, so the adjacent room temperature rises at night.  How would you cool this room?  Let's say the goal is to bring the temperature with everything running from a steady state of around 90 degrees down to 75 (equivalently, to offset the heat produced by ten 1U servers).
97475
Consider the  of Bennett et. al. How does one prove that this protocol would never violate the conservation of energy? At the face of it, it doesn't seem to be something obvious, as the various measurements, communications, rotations etc. don't seem to be able to account for the differences in the Hamiltonians of Alice's and Bob's labs. The state $\psi$ might have an expected energy $E_1$ in Alice's lab and a completely different expected energy $E_2$ in Bob's. Where does the difference come from?
13884
I am trying to achieve the strongest cooling effect using a TEC Peltier element.    Currently, my set up is two small, 20mm x 20mm peltier TES1-4902 run with a 5V 2.4A USB Battery Pack per peltier.   I need a way to reduce my costs while keeping the same cooling power.   Right now, it is expensive for me to run this set up due to the fact I need two batteries, and I am also looking to improve my efficiency while cutting out an entire battery and/or Peltier. The reason I have two separate battery packs is that I can not find a cheap, small, and thin battery pack that will output 4.8 Amps: however, putting two battery packs in a series may help eliminate one peltier.     So, I have a few branching question that center around a theme:  1) Would a larger Peltier allow for a stronger cooling effect as a result of a larger surface area, say like a 50MM x 50MM peltier, despite the fact (presumably) that it may be more difficult to cool one single peltier than 2 smaller, seperate ones?   2) Is there a Peltier size that would allow me to reduce my power consumption while maintaining a similar cooling effect?   3) Is there a way that I can output 5V 4.8A that is not in two separate USB battery packs that is small and relatively cheap, as battery price:output ability for small scale consumer is quite high and USB battery packs have been the cheapest source of sustainable power for me.    My problem stems from the fact that I am trying to pump as much power and achieve as much cooling power as possible without having to have, say, two battery packs and make the project too expensive. I need a way to reduce my costs while keeping the same cooling power.
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I'm trying to implement the main algorithm described in the . In order to do this, I have to create a quantum state $|x\rangle$ corresponding to a real vector stored in QRAM. I used an algorithm described more in detail in another paper, in which one can read:     For the runtime, there are $2^k$ rotations executed at the $k$-th level of the tree, apart from the last level where there are none. For a given level these rotations can be executed in parallel as they are all controlled operations on the same qubit, conditioned on different bit-string values of a shared register. To see this, let $U_x$ be a single qubit rotation conditioned on a bitstring $x \in \{0, 1\}^k$. Then the unitary $\bigoplus\limits_{x\in\{0,1\}^k} U_x$ applied to $|y\rangle\otimes|q\rangle$ achieves the desired parallel operation on the single qubit $|q\rangle$, where $|y\rangle = \sum\limits_{x\in\{0,1\}^k}\alpha_x\,|x\rangle$ is some superposition over bitstrings.   I'm not sure that I understand this notion of parallel execution. In the algorithm, at a given step $k$, one performs on one qubit $2^k$ controlled rotation conditionned on every qubit amongst the first $k-1$. Hence, we can summarize this as one big unitary matrix that acts on the first $k$ qubits, which will look-like $\begin{bmatrix}R_{\theta_1}&amp;0&amp;0\\\vdots&amp;\ddots&amp;\vdots\\0 &amp; 0 &amp; R_{\theta_{2^k}}\end{bmatrix}$, where for a given angle $\theta$, $R_\theta$ is the rotation of angle $\theta$ around the $Y$-axis of the Bloch sphere.  If we assume that this big operator is applied in $O(1)$, then I understand the notion of parallelism: you  don't have to successively apply the $2^k$ controlled gates, so you have a gain in complexity. But then, there is one problem I can't cope with. When you execute an algorithm on a quantum computer, I read that you are only allowed to use a specific set of gates. Hence, a compiler takes your code and transforms it to a compatible code. But am I sure that the compiler will always (or even sometimes) be able to decompose this big gate into a succession of smaller, allowed gates, without breaking the complexity?
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I am from a computer science background and I find it difficult to decide on the resources I should focus on while learning quantum computing, since there is so much to read/watch. My ultimate goal is to make a programming language acting as an interface between quantum computers and the person similar to 1972 when C was made. As a realistic intermediate stage, I would like to get to the point of writing programs on IBM's QISKit.  For that, I would need a schematic study guide in order to acquire the necessary background in Physics and the related fields required to dive into the field of quantum computing. Does this already exist: an ordered list of indispensable concepts and abilities to master, which if possible also mentions adequate material to acquire each of them?  Assume a high school level physics knowledge. Provide a study guide i.e. from beginner to expert kind of guide. Try to list video/book resources that one should follow in a chronological order so as to become an expert in the field of quantum computing to the level I can write my own quantum computing language (assuming already have other CS skills to write the language).
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I'm having a discussion with someone. I said that it is -even theoretically- impossible to reach $0$ K, because that would imply that all molecules in the substance would stand perfectly still.  He said that this isn't true, because my theory violates energy-time uncertainty principle. He also told me to look up the Schrödinger equation and solve it for an oscillator approximating a molecule. See that it's lowest energy state is still non-zero.  Is he right in saying this and if so, can you explain me a bit better what he is talking about.
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I am confused by a property.  In the N&amp;Chuang it is said that an $[n,k,2t+1]$ stabilizer code is able to correct up to $t$ errors. But for me if the code has distance $d$ it should be able to correct up to $d-1$ error.  Indeed, the distance of a quantum code is defined as the minimal weight of an element in $Z(S)-S$ (uncorrectable errors).  But then, if my error has a weight $d-1$, it is not in $Z(S)-S$ and I will be able to correct it ? Thus an $[n,k,d]$ code is able to correct up to $d-1$ error.  Where is my mistake ?