Questions tagged [annealing]

It is a metaheuristic for finding the global minimum of a given objective function over a given set of candidate solutions (candidate states), by a process using quantum fluctuations. (Wikipedia)

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Relationship of Adiabatic Quantum Computing speedup to Quantum Random Walk hit time

Considering the following two phenomena: Adiabatic quantum computing in general exhibits a quadratic speedup over classical simulated annealing, though for some Hamiltonians it may be faster (while ...
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Why is it so important to have uniform chain lengths in a minor embedding?

Very brief background In quantum annealing, the discrete optimization problem we wish to solve (such as finding the minimum of $b_1b_2 - 3b_1 + 5b_3b_4$ for binary variables $b_i$) may have a ...
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Are spin-glass problems NP (-complete)?

It is well known that finding ground states for spin-glass systems (Ising, XY...) is NP-hard (at least as hard as the hardest NP-problems) so that they can be efficiently used to solve other NP ...
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Adiabatic Quantum Computer e intermediate Hamiltonian evolves the state within the manifold

The Adiabatic Quantum Computer is implemented by slowly increasing the parameter s from 0 to 1 in the intermediate Hamiltonian $[\hat{H}(s) = \hat{H}_{input} + (1-s)\hat{H}_{init} + s\hat{H}_{circuit}]...
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In quantum adiabatic simulation, is the $s$ in $(1-\frac{s}{T})H_{in}+\frac{s}{T} H_{cl}$ related to the $t$ in $e^{-iHt}$?

I just want to do a whole adiabatic calculation on quantum circuit. To prepare two Hamiltonian of $H_{initial}$ and $H_{classical}$ and solve $H_{classical}$ using adiabatic calc like quantum ...
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What is the computational complexity of quantum annealing?

Quantum annealing can be thought of as a black box solver that can find approximate solutions to hard optimization problems. For example, D-Wave quantum annealers can approximately solve quadratic ...
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D-WAVE QUBO Matrix Form

I am trying to write down this problem (friend/enemy graph) in a polynomial matrix form in order to understand quantum annealing better, but it seems like the problem should actually be split into ...
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Can QAOA be considered as simulation of a quantum annealer on a gate-based quantum computer?

Quantum annealers are single purpose machines allowing to solve quadratic unconstrained binary optimization (QUBO) problems. QUBO problems have following objective function: $$ F=-\sum_{i<j}J_{ij}...
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Is either the adiabatic or the diabatic version of quantum annealing known to be theoretically more powerful than the other?

Quantum annealing can be considered either in the perfectly adiabatic "slow" limit (in which case it's usually referred as "adiabatic quantum computing" (AQC) instead of "...
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Is it absolutely necessary for Hamiltonians to not commute in QAA?

I have already read through the answers here. So I understand that if the Hamiltonians commute, then they have the same eigenstates but not necessarily the same energy eigenvalues. To formulate my ...
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What is an example of a simple QUBO problem?

I am digging into to the workings of the D-wave quantum annealing computers using this documentation. I find it very intuitive and well-explained, but their example of a "simple QUBO problem" does not ...
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How to convert a qubit hamiltonian to QUBO and vice versa?

This is my hamiltonian. Solving this by hand, Numpy Python package and VQE algorithm gives the minimum energy eigenvalue -2. If we want to find the minimum energy of this hamiltonian with Quantum ...
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Best route to learn quantum annealing as a beginner

My main goal is to learn Quantum annealing and quantum optimization in general. This concept is elaborated in this paper. A better example is this paper. I am particularly interested in reading ...
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Quantum Annealing - Random results on big N

I implemented a solver for the Job Shop Problem, based on quantum annealing, on a D-Wave machine. I have a problem, that even though minimal energy solutions exist, they are only chosen once. I set ...
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Quantum Annealing - Job Shop Problem

using this paper, I want to implement a solution for the Job Shop Problem on a D-Wave machine. One of the constraints mentioned in the paper, is $$ h_3(\bar{x}) = \sum_i \left(\sum_t x_{i,t}-1 \right)^...
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Entanglement and teleportation in quantum annealing and parallel computation

In classical optimization problems, some objective function's surface serves as a landscape for finding its minimum through minimization algorithms. Instead of your typical U-shaped objective ...
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Max eigenvalue algorithm via annealing starting from Gibbs state

In this talk, and the corresponding slides on page 24/44, Brandao talks about the max eigenvalue problem which is: Given a Hermitian $n\times n$ matrix $H$, approximate its largest eigenvalue. (Note ...
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Minimum Spanning Tree on D Wave Processor

I am attempting to implement a minimum spanning tree problem on the D wave quantum computing architecture. I have seen many graph problems implemented, such as a graph coloring example. There are also ...
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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,...
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How to calculate the $r^{\text{th}}$ digit of $\sum ^{j−1}_{p=i}d^p_{\pm k}$ using PyQUBO?

I am going to implement "turn circuit encoding" method of Coarse-grained lattice protein folding on a quantum annealer(Babej, Ing & Fingerhuth; 2018) using PyQUBO to run on the DWave qbsolv ...
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Is there an inherent difference in need for error correction between quantum annealing and gate based methods?

When I read about computing using gate based methods, I mainly read about the difficulties with error rates, circuit depth (and connectivity) and not enough qubits. With computing using quantum ...
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Q1Q2Q3Q4 coupling in qubo file

According to the question Q1Q2Q3 coupling in qubo file we can couple 3 qbits. When it comes with 4 qbits like q1q2q3q4, how should set this 4-qbit element to qubo file?
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Q1Q2Q3 coupling in qubo file

When we expand the Ising model we have one component with 3 qbits like Q1Q2Q3. But in qubo file we can only set coupling for 2 qbit only. How should I set this 3-qbit element to qubo file?
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What are techniques are used to esimate the spectral properties of annealer embedding hamiltonians?

Some information about the spectral properties of the hamiltonian of a given annealer emebedding is needed to determine a proper annealing schedule, correct? What are methods that are used to find ...
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Are there established best practices for designing Dwave embeddings?

Some of my larger annealer embeddings (~200 qubits) don't anneal down to the ground state while some of them do very easily. Are there established guidelines for designing annealer embeddings to ...
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Can quantum annealing be used for training convolutional neural networks?

Simulated annealing is applied for deep learning using convolutional neural networks. Likewise, can quantum annealing be used? These two papers: Simulated Annealing Algorithm for Deep Learning (...
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When and where was the first use of the term Chimera?

This is along the same lines as the earlier question: When was the first use of the word Entanglement? I was surprised to discover that when searching for "chimera" in both of Vicky Choi's minor-...
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What's a Qubit on D-Wave 2000Q?

From D-Wave flyer: The D-Wave 2000Q system has up to 2048 qubits and 5600 couplers. To reach this scale, it uses 128,000 Josephson junctions, which makes the D-Wave 2000Q QPU by far the most ...
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Can quantum annealing find excited states?

If we start with a Hamiltonian $H(t_i)$, and with our qubits prepared in the ground state of this, and then slowly change this to a Hamiltonian $H(t_i)$, the final state of our qubits should be the ...
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Adiabatic Quantum Computing vs Adiabatic Quantum Optimization vs Quantum Annealing

I am aware that of the difference of Adiabatic Quantum Computing (AQC) and Quantum Annealing (QA) as explained here. However, another term which came up in some papers was Adiabatic Quantum ...
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Gradient boosting akin to XGBoost using a quantum device

I am currently trying to implement a boosting algorithm akin to XGBoost with a quantum device. The reason is that I want to make use of a quantum device to train weak classifiers. However, as far as I ...
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What precisely is Reverse Annealing?

Quantum Annealing, (related questions Quantum Annealing, or hamiltonian related) is the process used in D-Waves' Quantum Annealer, in which the energy landscapes are explored, for different solutions, ...
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Why is it crucial that the initial Hamiltonian does not commute with the final Hamiltonian in adiabatic quantum computation?

I've read in many sources and books on adiabatic quantum computation (AQC) that it is crucial for the initial Hamiltonian $\hat{H}_i$ to not commute with the final Hamiltonian $\hat{H}_f$, i.e. $\left[...
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How can a D-Wave style Annealing QPU help sampling?

This question is a follow-up on this one, with the hope of getting more specific clues, and was motivated by this answer by user Rob. Also please note this posts that handle the topic of QA in much ...
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What precisely is quantum annealing?

Many people are interested in the subject of quantum annealing, as an application of quantum technologies, not least because of D-WAVE's work on the subject. The Wikipedia article on quantum annealing ...
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What is the difference between quantum annealing and adiabatic quantum computation models?

From what I understood, there seems to be a difference between quantum annealing and adiabatic quantum computation models but the only thing I found on this subject implies some strange results (see ...
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Assessing speed-up via Quantum-Stochastic correspondence

You can make a natural correspondence between a quantum state vector and a classical probability vector, and between a quantum unitary operator and a classical stochastic matrix. There is also a ...
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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 ...
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Hardware wise, how does D-Wave achieve quantum annealing?

Quantum computers have shown a new way to compute old problems. D-Wave has a quantum annealer, and Wikipedia describes the D-Wave quantum computer and its use of quantum annealing properties. ...
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Is there proof that the D-wave (one) is a quantum computer and is effective?

I'm admittedly a novice in this field, but I have read that, while the D-wave (one) is an interesting device, there is some skepticism regarding it being 1) useful and 2) actually a 'quantum computer'....
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How long does quantum annealing take to find the solution to a given problem?

Quantum annealing is an optimization protocol that, thanks to quantum tunneling, allows in given circumstances to maximize/minimize a given function more efficiently than classical optimization ...
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Level of advantage provided by annealing for traveling salesman

My understanding is that there seems to be some confidence that quantum annealing will provide a speedup for problems like the traveling salesman, due to the efficiency provided by, ex, quantum ...
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Why can't quantum annealing be described by a gate model?

This is a question I was inspired to ask based on this question, which notes that quantum annealing is an entirely different model for computation than the usual circuit model. I've heard this before, ...
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How much faster is “D-Wave Two” compared to its predecessor?

I don't have any specific task or algorithm in mind, so depending on how they were tested – Is there any research which shows just how the D-Wave Two computer was faster (in terms of computation ...