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What is meant by "Noisy Intermediate-Scale Quantum" (NISQ) technology?

When we talk about quantum computers, we usually mean fault-tolerant devices. These will be able to run Shor's algorithm for factoring, as well as all the other algorithms that have been developed ...
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13 votes

How should different quantum computing devices be compared?

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 - ...
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8 votes

How should different quantum computing devices be compared?

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 ...
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7 votes

How should different quantum computing devices be compared?

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 ...
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6 votes

What use has quantum computing been?

There are a lot of interesting applications that use similar technology. A lot of labs that work towards quantum computing also publish papers with these applications. Here are some: All-optical ...
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6 votes
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Quantum speedup in Bayesian machine learning on NISQ computers

As far as I know, there are four possibilities for having a quantum advantage in Bayesian machine learning: Gaussian processes: there is a known quantum speed-up for Gaussian processes that you can ...
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6 votes
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What's the point of VQE if classical computers can solve for eigenvalues easily?

The computational advantage of using quantum computers can be reached if the classical resources (memory; number of operations), required to solve a particular problem, grow exponentially in a certain ...
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5 votes
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NISQ algorithm: do they all have circuit updated between each run AND impossible to predict when they will stop?

What you described is the class of Variational Quantum Algorithms. Variational Quantum Eigensolver (VQE) and QAOA (Quantum Approximate Optimization Algorithm) are belong into this class. Says, you ...
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Pennylane and Qiskit for quantum machine learning

Have a look at these for quantum machine learning: Supervised learning with quantum computers by Schuld and Petruccione (2018) An introduction to quantum machine learning by the same authors of the ...
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5 votes
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Where does the Xmon simulator from Googles cirq framework its entropy from?

Cirq uses numpy's pseudo random number generator to pick measurement results, e.g. here is code from XmonStepper.simulate_measurement: ...
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5 votes
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How should different quantum computing devices be compared?

I think the answer depends on why you are comparing them. Things like the quantum volume, are perhaps better suited to defining progress in the development of devices rather than fully informing end ...
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5 votes
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What use cases are there for 127 qubit QPUs?

I think that the main reason behind is to tackle technical difficulties connected with building huge number of qubits. Having hundred of qubits brings about issues with interconnection, connections to ...
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4 votes

What use has quantum computing been?

Perform and checking basic quantum-mechanic experiments Before the IBM and alibaba quantum cloud computers, you would need an expensive lab to do simple CHSH or GHZ experiments. Of course the qubits ...
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4 votes
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Devising "structured initial guesses" for random parametrized quantum circuits to avoid getting stuck in a flat plateau

I am not an expert but I read a few papers and here is what I have found. Similarly to NN, people found strategies to avoid this issue with the gradients. Basically, for some problems, you can use ...
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4 votes
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Minimum number of CNOTs for a 4-qubit increment on a planar grid

Here is the best circuit I've found. It uses 14 CNOTs. Note that this circuit is not using a linear layout! It is placed on the grid like this: ...
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3 votes
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What are the libararies for Machine Learning on NISQ Chip? And What are the roadmaps?

You will have very limited support simulating photonic circuits in Cirq (and therefore Tensorflow Quantum). Those libraries mainly deal with evolving systems of qubits where a state $|\psi\rangle$ is ...
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3 votes

Quantum Machine Learning in NISQ era

I will give you a partial answer cocerning using quantum machine learning methods in NISQ era. As any other quantum algorithm, QML algorithms can be used on current NISQ processors. However, there is ...
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3 votes

Gate SWAP vs Physical SWAP in Trapped Ions for chain reordering

Prelim: I am no expert on implementation techniques or the frontier of what gate technology is being used in current renditions of Trapped Ion QC. The Molmer-Sorensen gate is generally what is used in ...
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3 votes

What use has quantum computing been?

Thinking about the theoretical capabilities of quantum computers has led to important insights on the theory of classical computers. One example is the proof that the (classical) complexity class PP ...
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  • 2,107
3 votes

Is it possible to efficiently measure outer products of quantum states, of the form $|a\rangle\langle b|$?

This outer product is, in general, not Hermitian and so does not correspond directly to a physical observable. Taking a lesson from $2\times 2$ matrices (ie from polarimetry), we can measure the two ...
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2 votes

Most efficient way for general state generation

For completely arbitrary coefficients you are out of luck. A simple counting argument says that because: 1) The coefficients are continuous parameters 2) gates implement discrete operations $\to$ ...
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  • 549
2 votes

What use has quantum computing been?

Executing a NISQ-device in a manner that asymptotically outperforms a classical computer invalidates the Extended Church-Turing Thesis (ECT). Voluminous tomes written about the (non-extended) Church-...
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  • 7,404
2 votes

Pennylane and Qiskit for quantum machine learning

Since quantum machine learning with NISQ hardware is such a relatively new field, it is still very highly research driven, and a lot of the potential is still being determined. To make these new ...
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2 votes

What is the implication of locality in QAOA?

Consider a nearest-neighbor Ising Hamiltonian $$H = \sum_{i=1}^n J_i \sigma_i^z \sigma_{i+1}^z.$$ Let $X = \sum_{i=1}^n \sigma_i^x$. The QAOA ansatz is $$|\mathbf{\beta}, \mathbf{\gamma}\rangle = \exp\...
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  • 61
2 votes

How is back-propagation done in "Transfer learning in hybrid classical-quantum neural networks"

How is back-propagation done through the classical weights feeding into the quantum unitaries? In this particular case, the gradient of the quantum variational circuit is computed using the parameter-...
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2 votes

What are the libararies for Machine Learning on NISQ Chip? And What are the roadmaps?

Here's some examples: IBM: Aqua Google: Tensor-Quantum Xanadu: PennyLane
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2 votes

What is the "quantum mean value problem"?

The (additive) quantum mean value problem can be defined this way: Given any constant $\epsilon > 0$, Hermitian observables $O_1,...,O_n$, and constant depth quantum circuit $U$ on $n$ qubits, ...
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1 vote

Mahadev's classical homomorphic encryption for quantum circuits and NISQ computing

There are two arguments for why it is not possible to use NISQ to implement Mahadev's scheme. The first one is that it is not intrinsically tolerant to errors. Meaning that very quickly on a NISQ ...
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1 vote

Design NISQ Circuit with StrawberryFields

Ok It is done and it is correct. I just forgat to give an initial state to the program like Ket(initial_state) | q And after that I also added a BSGate for 1 and ...
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  • 446
1 vote

Quantum Machine Learning in NISQ era

Quantum Machine Learning in this NISQ Era is making progress in the problems related classification, categorisation, clustering, and optimisation areas for specific type of datasets in chemistry, ...
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