Questions tagged [optimization]

For questions concerning how to improve quantum computers on different aspects like performance, efficiency or fault-tolerance.

Filter by
Sorted by
Tagged with
4 votes
2 answers

What does it mean to have 2000 qubits and 6016 couplers?

From official D-Wave docs: The D-Wave 2000Q QPU has up to 2048 qubits and 6016 couplers. For example, I have the optimization problem defined as the QUBO problem. If I want to solve it on D-Wave,...
Kenenbek Arzymatov's user avatar
4 votes
0 answers

Genetic algorithm does not converge to exact solution

I'm trying to evolve quantum circuits using genetic algorithms as they did in this paper Decomposition of unitary matrices for finding quantum circuits: Application to molecular Hamiltonians (Daskin &...
Fernando's user avatar
  • 247
3 votes
1 answer

Evolving a quantum circuit using a genetic algorithm

I've written a small quantum circuit simulator in python, so now I'm trying to evolve some circuits via genetic algorithms. My encoding is very simple, it's just a rectangular table of strings ...
Fernando's user avatar
  • 247
3 votes
1 answer

Optimise implementation of a quantum algorithm when an input is fixed

I need to implement a quantum comparator that, given a quantum register $a$ and a real number $b$ known at generation time (i.e. when the quantum circuit is generated), set a qubit $r$ to the boolean ...
Adrien Suau's user avatar
  • 4,702
2 votes
1 answer

Optimal sampling strategy for VQE

In VQE we wish to minimize some cost function $F(\vec{x})$ that is dependent on a quantum state $\left| \psi_\vec{x} \right>$ which is prepared by a unitary $U(\vec{x})$ depending on some (...
Jan Lukas Bosse's user avatar
5 votes
2 answers

Resources on hybrid quantum-classical algorithms applied to combinatorial optimization problems

I am doing a thesis on "Metaheuristics and Quantum Computing", and was wondering if anyone could recommend some papers/pages to read talking about hybrid quantum/classical computing. (My idea is to ...
Pedro Pepê's user avatar
1 vote
1 answer

Applying Group Leaders Optimization to Quantum Belief Systems

Context: I am particularly interested in quantum cognition & would like to use a tool like pyZX to perform the following types of optimizations. In Preparing a (quantum) belief system they "...
user820789's user avatar
  • 3,272
8 votes
1 answer

Understanding the Group Leaders Optimization Algorithm

Context: I have been trying to understand the genetic algorithm discussed in the paper Decomposition of unitary matrices for finding quantum circuits: Application to molecular Hamiltonians (Daskin &...
Sanchayan Dutta's user avatar
3 votes
3 answers

How to run algorithms on IBMQ via Qiskit-Aqua?

I am trying to run an optimization problem on IBMQ. Running the same code on QASM simulator works fine. However, changing only the backend name to IBMQX takes long time. I am aware of the queues ...
Akshay Ajagekar's user avatar
10 votes
1 answer

Minimum number of CNOTs for a 4-qubit increment on a planar grid

Recently I've been wondering how high NISQ machines will be able to "count". What I mean by that is, given the most optimized increment circuit you can make, how many times can you physically apply ...
Craig Gidney's user avatar
11 votes
4 answers

Minimum number of CNOTs for Toffoli with non-adjacent controls

I want to decompose a Toffoli gate into CNOTs and arbitrary single-qubit gates. I want to minimize the number of CNOTs. I have a locality constraint: because the Toffoli is occurring in a linear array,...
Craig Gidney's user avatar
5 votes
0 answers

Application of classical approximate optimization algorithm to bottlenecks of quantum computing

According to J. Gough, one of the bottlenecks in the current development of large-scale quantum computing may be the lack of our ability to simulate large scale quantum system, which is a NP-hard ...
Math.StackExchange's user avatar
10 votes
1 answer

Barren plateaus in quantum neural network training landscapes

Here the authors argue that the efforts of creating a scalable quantum neural network using a set of parameterized gates are deemed to fail for a large number of qubits. This is due to the fact that, ...
asdf's user avatar
  • 493
11 votes
1 answer

Devising "structured initial guesses" for random parametrized quantum circuits to avoid getting stuck in a flat plateau

The recent McClean et al. paper Barren plateaus in quantum neural network training landscapes shows that for a wide class of reasonable parameterized quantum circuits, the probability that the ...
Daniel Yaacov's user avatar
11 votes
1 answer

Is there any general statement about what kinds of problems can be approximated more efficiently using a quantum computer?

As the name already suggests, this question is a follow-up of this other. I was delighted with the quality of the answers, but I felt it would be immensely interesting if insights regarding ...
fr_andres's user avatar
  • 744
13 votes
1 answer

What is the difference between QAOA and Quantum Annealing?

Edward Farhi's paper on the Quantum Approximate Optimization Algorithm introduces a way for gate model quantum computers to solve combinatorial optimization algorithms. However, D-Wave style quantum ...
hopefully coherent's user avatar

1 2 3