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27

I was looking for why optical quantum computers don't need "extremely low temperatures" unlike superconducting quantum computers. Superconducting qubits usually work in the frequency range 4 GHz to 10 GHz. The energy associated with a transition frequency $f_{10}$ in quantum mechanics is $E_{10} = h f_{10}$ where $h$ is Planck's constant. Comparing the ...


26

Firstly, a classical computer does basic maths at the hardware level in the arithmetic and logic unit (ALU). The logic gates take low and high input voltages and uses CMOS to implement logic gates allowing for individual gates to be performed and built up to perform larger, more complicated operations. In this sense, typing on a keyboard is sending ...


19

Is a dilution refrigerator the only way to cool superconducting qubits down to 10 millikelvin? There's another type of refrigerator that can get to 10 mK: the adiabatic demagnetization refrigerator (ADR).$^{[a]}$ why is dilution refrigeration the primary method? To understand that, let's talk about one of the main limitations of the ADR. How an ADR ...


15

Here is my process for doing arithmetic on a quantum computer. Step 1: Find a classical circuit that does the thing you're interested in. In this example, a full adder. Step 2: Convert each classical gate into a reversible gate. Have your output bits present from the start, and initialize them with CNOTs, CCNOTs, etc. Step 3: Use temporary outputs. If ...


14

Well, first, not all systems must be kept near absolute zero. It depends on the realization of your quantum computer. For example, optical quantum computers do not need to be kept near absolute zero, but superconducting quantum computers do. So, that answers your second question. To answer your first question, superconducting quantum computers (for example) ...


14

This is a greatly debated topic, and I'm not sure there is an answer to your question at the current time. However, the IEEE (Institute of Electrical and Electronics Engineers) has proposed PAR 7131 - Standard for Quantum Computing Performance Metrics & Performance Benchmarking: The purpose of this project is to provide a standardized set of ...


12

The transmon is a Josephson junction and capacitor in parallel. Originally, transmons were differential circuits, i.e. two transmons on the same chip were not galvanically connected in any way. In other words, transmons didn't share a ground reference. Furthermore, in the early days, transmons were almost always embedded into the middle of a harmonic ...


11

This section on Wikipedia collects the most important ongoing attempts to physically implement qubits. For physically implementing a quantum computer, many different candidates are being pursued, among them (distinguished by the physical system used to realize the qubits): Superconducting quantum computing (qubit implemented by the state of ...


10

What you call a black box is simply isolating the quantum system that stores (or represents) your qubits from the environment. This can be done in several ways depending on your physical realization. For example, in an ion trap based quantum computer, one uses states of a single ion to represent a qubit, and isolates that from the environment by levitating ...


9

While number of qubits should be part of such a metric, as you say, it's far from everything. However, comparing two different completely different devices (e.g. superconducting and linear optics) is not the most straightforward task1. Factors Asking about coherence and gate times is equivalent to asking about fidelity and gate times1. Gates being harder ...


9

That is indeed the most important question at the moment! Superconducting qubits currently have the biggest devices. But will they continue to scale? Will short coherence times make it too hard for error correction to keep up? Trapped ions are not far behind. But they have their own scalability issues. Spin qubits should be great for scaling once they get ...


9

If your intent is to understand Gil Kalai's arguments, I recommend the following blog post of his: My Argument Against Quantum Computers: An Interview with Katia Moskvitch on Quanta Magazine (and the links therein). For good measure, I'd also throw in Perpetual Motion of The 21st Century? (especially the comments). You can also see the highlights in My ...


8

$\require{\mhchem}$ There are almost too many ion species to list that have been used in ion trap based quantum computing or related experiments. The usual choice is one that is, when singly ionized, hydrogen-like which has convenient consequences for their laser spectroscopy: Then a strong, typically $20$ MHz wide transition lies in the UV or blue end of ...


8

Pressure implies the presence of stray atoms flying around messing things up. The use of a vacuum is required to prevent this, as one of the ways of keeping the device well isolated from unwanted effects. I think that they are just intending the "10 billion times lower than atmospheric pressure" statement to demonstrate how good their vacuum is.


8

As a start, you might want to look at https://arxiv.org/abs/1605.03590, which lays out conservative (i.e., high) qubit and gate requirements for a meaningful quantum chemistry calculation under some pretty reasonable assumptions. The estimates there are on the order of $10^{15}$ total logical gates (not gate depth) over roughly 100 logical qubits, which ...


7

Because light, at the right frequencies, interacts weakly with matter. In the quantum regime, this translates to single photons being largely free of the noise and decoherence that is the main obstacle with other QC architectures. The surrounding temperature doesn't disturb the quantum state of a photon as much as it does when the quantum information is ...


7

As usual, it is too soon to make comparisons like this. The power consumption of a device will depend strongly on the architecture it uses, for one. However, in principle, there is no reason to suspect that quantum computers would consume more energy than classical devices performing the same operations. Indeed, one would expect the opposite, the ...


7

The answer to noise (and any source of error, really) in quantum computations is quantum error correction: You choose an encoding such that discretized errors correspond not only to invalid encodings but also uniquely determine what kind of error must have occured. This is not possible for all errors but with reasonable error models (such as single qubit ...


7

You may want to check out this Schaetz et al, Reports on Progress in Physics of 2012 "Experimental quantum simulations of many-body physics with trapped ions" (alternate link in semanticscholar). In sum: yes, the arrangement of the ions is one key limitation to scalability, but no, configurations are not currently limited to a single line of atoms. On that ...


7

Ion trap quantum computers hold ions in empty space using electric not magnetic fields. That is impossible using static fields (Earnshaw's theorem) so an alternating field is used. The effect is that charged particles such as ions seek a field minimum; this type of ion trap is also called a quadrupole trap because the simplest (lowest order) field having a ...


7

Disclosure: while I am not an experimental physicist, I am part of the NQIT project, which is aiming to develop quantum hardware which is suitable to realise scalable quantum computers. The architecture that we're investing most heavily in is optically linked ion traps. Ions represent some of the physically best understood systems to experimental and ...


7

Quantum volume is likely only useful as a metric for small noisy computers. It’s impossible to invent any single-number metric that’s ideal for all tasks. Even with classical computers, metrics such as Dhrystone or Windows Performance Index are at best suggestive at predicting performance on real-world tasks. Conversely, giving more than one number can ...


6

How do we prevent quantum noise in a quantum computer? Well, technically the answer is (at least for most systems): we use ridiculously low temperatures (much colder than space), we shield everything (or at least as much as possible) out, that might introduce any noise (radio waves, such as phone signals or light, magnetic fields, ...), we do everything to ...


6

While I’m not an experimentalist, and have not studied these systems in any great depth, my (crude) understanding is the following: In ion traps you (more or less) have to trap the ions in lines. However, this isn’t a limitation in terms of the ease of communication because what you’re probably thinking about is when a linear system has nearest neighbour ...


6

Sort of, quite possibly, if by degrees This is a speculative, but plausible, answer First of all, how do qubits interact and states evolve with time? The description of how individual qubits evolve (i.e. a single qubit gate operation) is given by some Hamiltonian1. Multiple, non-interacting qubits (that are exactly the same) therefore evolve using ...


6

IBM is promoting their quantum volume (see also this) idea to quantify the power of a gate model machine with a single number. Before IBM, there was an attempt from Rigetti to define a total quantum factor. Unclear if it captures what we want in terms of usefulness of devices for applications. Things such as quantum volume are be designed with supremacy ...


6

Taking an $n$-mode simple harmonic oscillator (SHO) in a (Fock) space $\mathcal F = \bigotimes_k\mathcal H_k$, where $\mathcal H_k$ is the Hilbert space of a SHO on mode $k$. This gives the usual annihilation operator $a_k$, which act on a number state as $a_k\left|n\right> = \sqrt n\left|n-1\right>$ for $n\geq 1$ and $a_k\left|0\right> = 0$ and ...


6

"Is Quantum Biocomputing ahead of us?" There has been some work done on biocomputing, quantum computing, spin chemistry, and magnetochemical reactions. Correlated radical pairs — pairs of transient radicals created simultaneously, such that the 2 electron spins, one on each radical, are correlated — on photoactive magnetoreceptive proteins such as ...


6

Again, this is still an open question. There are two lines of work that come to mind when you talk of "hardware-based neural networks" which try/claim to use photonics as a mean to speed-up processing, and make direct reference to speeding up machine learning tasks. Shen et al. 2016 (1610.02365) propose a method to implement "fully-optical neural networks" ...


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