# Tag Info

12

This is discussed in chapter 5 of Ciliberto et al.. The purpose of most quantum(-enhanced) machine learning algorithms is to speed-up the processing of classical data over what is possible with classical machine learning algorithms. In other words, the context is that you have a set of classical vectors $\{\boldsymbol x_k\}_k$, and you want to compute some ...

12

A good summary on the current state of QRAM (as of 2017) can be found in this paper, and a comparison of it with classical methods can be found in this talk. The Giovannetti type "bucket brigade" QRAM still seems to be the best that is known, although modifications exist. There are serious caveats to the use of any such QRAM, and no alternative that avoids ...

11

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 ...

10

In summary, no. If you think about it, this makes sense. When measuring a quantum system with $n$ qubits, you get $n$ bits of information. the $2^n$ figure exists only when the system is in superposition, which a classical computer cannot access. The specific theorem in question here is Holevo's theorem. To quote Wikipedia: In essence, the Holevo bound ...

6

Unfortunately the state of the technology regarding memories is not as developed as you seem to expect. When we talk about a memory, we think of a device that can store information for an infinite amount of time (for all practical purposes). So before we can think about the size of the memory in a quantum computer, we should look at whether a single quantum ...

4

It's not so much a matter of big data, but that of saving data. Quantum storage is still (much like the rest of the field) in its infancy. (Take what I write with a grain of salt. It's likely to change rapidly.) There are a few theories on how quantum computers might be able to hold "memory". One of these is using nuclear spin. E.g. using long-lived ...

4

They say that this scheme requires to throw $O(N)$ switches for each memory call, but I don't understand why is this the case. From the above, it would seem that one just needs to throw $O(\log_2(N))$ switches, one per bifurcation, to get from the top to the bottom. It seems to me that $n= \log_2 N$ is the length of the address register: the number of ...

3

If you are looking for implementations of quantum memories, you can find a few in this QRAM library for Q#. I am not quite sure what you mean by the bucket brigade protocol is not able to readout entangled data, but as far as I understand you can do that with bucket brigade (we used it in this example that implements Grover's algorithm with a bucket brigade ...

3

According to comment provided by user gIS, there was no progress in implementing qRAM as proposed in the paper. However, some additional information on qRAM physical implementation can be found on this forum here.

3

Partial answer (why qRAM is useful) Currently, quantum computers do not have an operational memory. Quantum processor is composed of qubits which can be considered to be an elementary memory. However, they are rather used for performing calculations. There is no way how to save intermediate results. Of course, you can measure an output of the quantum ...

3

Your question revolves implicitly around the concept of quantum decoherence and how to protect real-world implementations of qubits from it for a long time. This is an incredibly general problem, and at the same time, the details are wildly dependent on the technology used. If you have access to it, you can check chapter 5 : "Noise and decoherence" of ...

3

Yes, you can encode a program into your qubits in exactly the same way you'd encode a program into bits and then run circuits that interpret the program. One might hope that you could encode the program in some fancy exponentially efficient way, but in Mike&Ike they prove that's not possible. Because there's no exponential advantage, and because the ...

2

An answer to this question seems to have been given by the same authors, in a different follow-up paper which I hadn't seen before. In [1], the authors write (emphasis mine): A classical RAM that uses the bucket-brigade addressing schemes need only activate $O(n)$ transistors in the course of a memory call, in contrast with a conventional RAM that ...

2

Typically, quantum search algorithm searches through a very large solution spaces that can represented by logarithmic scale of data, not directly over huge amount of data. An example is travelling salesman problem where the input data are the distances between cities, but each solution is a path and the space to be searched is exponential in terms the number ...

2

Qiskit and other programming languages allow to write a hybrid algorithms, i.e. combination of classical and quantum algorithm. Inputs to quantum algorithm can be pre-processed on classical computer and results produced by quantum computers can be post-processed again classically. You are right that storage is still a problem. So far quantum RAM (qRAM) was ...

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You seem to be thinking about "quantum memory" like it is one specific thing and there is only one specific way it can happen. In reality, what you describe is a valid notion of quantum memory. Another popular one, involving the element Yb, is this one: https://arxiv.org/abs/1701.04195.

1

I think the point is that many quantum algorithms prove/are believed to be efficient to process data when said data is encoded in a quantum state. An easy example of this being Grover, which produces (with high probability yada yada yada) the state $|x\rangle$ corresponding to the $x$ such that $f(x)=1$ for some given "oracle function" $f$. But the ...

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