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Description:
qubo embedder
An unofficial library to embed and send optimization (QUBO, Ising) problems to DWave System quantum annealing solvers. A native Dart equivalent to the Ocean SDK.
TABLE OF CONTENTS
Usage
Send to remote DWave annealer solver
Sample using local simulator
Data structures
Qubo
Hamiltonian
SolutionVector
SolutionRecord
DWave API
Interact with the API manually
Embedding types and algorithms
Encoding and decoding
Usage #
Solving QUBO problems is handled by the Solver class which has different modes. Assuming you have your data prepared, it's relatively easy to get your solutions:
Send to remote DWave annealer solver #
await Solver.dwaveSampler(
region='eu-central-1'
solver='Advantage_system5.3',
token='[YOUR_API_TOKEN]',
).sampleQubo(
qubo,
)
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This takes care of the embedding, API calls etc. automatically.
Sample using local simulator #
Solver.simulator().sampleQubo(
qubo,
record_length=5,
)
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Data structures #
You can format your problems using built-in data types. These use the ml_linalg package internally to provide fast and efficient handling of linear algebra types and operations, especially in the Solver.simulator() solver.
Qubo #
Add the coefficients of your QUBO-problems using the indices of the affected variables (beginning at 0).
import 'package:qubo_embedder/qubo_embedder.dart';
void main() {
var qubo = Qubo(size: 2);
qubo.addEntry(0, 0, value: 2.0);
qubo.addEntry(1, 1, value: 2.0);
qubo.addEntry(0, 1, value: -2.0);
// qubo.addEntry(1, 0, value: 2.0) throws an InvalidOperationException
print(qubo.getEntry(0, 1)); // -2.0
print(qubo); // [qubits: 2] {(0, 0): 2.0, (0, 1): -2.0, (1, 1): 2.0}
}
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Hamiltonian #
If you're done, you can transform Qubo objects to Hamiltonian which the samplers take as an input.
import 'package:qubo_embedder/qubo_embedder.dart';
void main() {
var hamiltonian = Hamiltonian.fromQubo(qubo);
print(hamiltonian.matrix) // [[2.0, -2.0], [0.0, 2.0]]
}
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SolutionVector #
This type you seldom have to create for yourself, but is used by the solvers to return the solutions to a QUBO problem. A solution vector is immutable, but can be transformed into a regular list.
import 'package:qubo_embedder/qubo_embedder.dart';
void main() {
var solutionVector = SolutionVector.fromList([0, 1]);
print(solutionVector.vector); // [0, 1]
print(solutionVector); // [q0: 0, q1: 1]
}
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SolutionRecord #
Sampler store their solutions as entries in this record, which you can get by entries() and iterate over for solution details. When returned by a sampler, the entries are sorted by energy in ascending order.
import 'package:qubo_embedder/qubo_embedder.dart';
void main() {
...
for (var entry in solutionRecord.entries()) {
print("E=${entry.energy}\t${entry.solutionVector}\t${entry.numOccurrences}x")
} // E=-2.0 [q0: 0, q1: 1, q2: 1, q3: 0, ] x142
print(solutionRecord);
// energy sample occurrences
//(1) -2.0 [q0: 0, q1: 1, q2: 1, q3: 0, ] x142
}
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DWave API #
Sometimes, pre-defined samplers aren't enough. For specific operations and scenarios not covered by Solver, you can use the DwaveApi class to gain low-level access to the DWave REST Solver API, sending and managing requests directly.
Interact with the API manually #
Here, a list of currently available solvers is requested:
import 'package:qubo_embedder/qubo_embedder.dart';
final _params = ApiParams(apiRegion: 'eu-central-1', apiToken: '[YOUR_API_TOKEN]');
Future<void> main() async {
List<QpuSolverInfo> solvers = await DwaveApi.getAvailableQpuSolvers(_params);
print(solvers[0].name) //Advantage_system3.5
print(solvers[0].numQubits) //5616
}
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You can go from there and, for example, select the solver with the highest count of qubits available and supply it to DwaveSampler. Keep in mind that DwaveApi only offers static wrappers to selected API requests, returning an awaitable Future. Encoding and decoding of body properties is done automatically (see Encoding and decoding).
Embedding types and algorithms #
If needed, embeddings can also be intercepted by creating it yourself. Currently supported are PseudoEmbedding (faster, but will only work for a problem size up to 4) and MinorEmbedding (slower, but works on all problems as long as the physical qubits are not exhausted), which both are descendants of the Embedding superclass. Embeddings can't be instantiated directly but have to be created by Embedder, depending on the supplied algorithm.
Embedder.embedQubo(
qubo: qubo,
graphInfo: graphInfo, //Retrieved from the DWave API
type: EmbeddingAlgorithm.pseudo,
);
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An embedding consists of a map of physical qubit IDs with their respective bias and a map of couplers with their respective bias.
Encoding and decoding #
This utility class is used by DwaveApi internally, but can be accessed directly as well if needed. The DWave Rest Solver API accepts and returns problem data only in bit-packed, base64-encoded form, for which the Encoder and Decoder classes offer conversion methods that utilize the binary package for performance.
SAPI body parameter
Codec
Corresponding method
Submission
data.lin
Base64-encoded, little-endian 8-byte floating point numbers
Encoder.encodeDoubles()
data.quad
Base64-encoded, little-endian 8-byte floating point numbers
Encoder.encodeDoubles()
Retreival
answer.solutions
Base64-encoded bits in little-endian order, each padded to end on a byte boundary
Decoder.decodeBinary()
answer.energies
Base64-encoded, little-endian 8-byte floating point numbers
Decoder.decodeDoubles()
answer.num_occurrences
Base64-encoded, little-endian 4-byte integers
Decoder.decodeInts()
answer.active_variables
Base64-encoded, little-endian 4-byte integers
Decoder.decodeInts()
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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