Project: All struct fields should be (concretely) typed (potentially with a type parameter) [$200]

Many of the symbolic types in this library are rather clumsily defined, without much attention being paid to the types of their fields. The goal of this bounty is to specify them and parameterize them as much as possible and reasonable, in preparation for next steps like the use of sum types and Unityper.jl. This forum discussion might provide useful background.

Required skills: Understanding of Symbolics.jl and Julia's type system

Reviewer: Stefan Krastanov

Duration: 1 month

Payout procedure:

The Funding for these bounties comes from the National Science Foundation and from the NSF Center for Quantum Networks. The payouts are managed by the NumFOCUS foundation and processed in bulk once every two months. If you live in a country in which NumFOCUS can make payments, you can participate in this bounty program.

Click here for more details about the bug bounty program.

we already have

julia> Set([X1, X2]) == Set([X1, X2])
true

julia> Set([X1, X2]) == Set([X1, Z1])
false

Set uses hashing for quick (potentially false positive) equality check in inclusion (log(n)), followed by isequal check to avoid false positive. Thus set equalities have cost of n log(n) instead of n^2 without the use of a smart datastructure.

Initially there was a worry that Set uses ==, which would have broken its use with Symbolics (where == is used to create a symbolic equation), but that does not seem to be the case.

To avoid creating a new Set at every equality check, we should probably have it as part of the structure. E.g.

@withmetadata struct SAdd{T<:QObj} <: Symbolic{T}
    dict
    _set_precomputed
    _arguments_precomputed
end

It will take a bit more memory (not much given that the objects are not copied, only referenced), but it should speed up a lot of other code.

pinging @apkille as we had been discussing this in #40

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Project: "Thorough benchmarks" [$200]

We have a small benchmark suite already implemented for our other repositories, which is executed as part of our CI runs. It is defined in the benchmark folder and reported for each pull request. We would like to implement a similar benchmark suite here to include many facets of this library. E.g. basic symbolic operations, simplifications, rule application, flattening and expanding, expressing into numerical backends, time to import, etc. The new benchmarks should be legible, easy to follow, and organized by topic. Most of them should be microbenchmarks testing only one concept, but a few holistic benchmarks would make sense as well.

Required skills: Generic Julia skills.

Reviewer: Stefan Krastanov

Duration: 1 month

Payout procedure:

The Funding for these bounties comes from the National Science Foundation and from the NSF Center for Quantum Networks. The payouts are managed by the NumFOCUS foundation and processed in bulk once every two months. If you live in a country in which NumFOCUS can make payments, you can participate in this bounty program.

Click here for more details about the bug bounty program.

Move the test runner to use TestItems.jl [$200]

[TestItems.jl](Move the test runner to use TestItems.jl [$200]) permits more convenient execution of tests from withing an IDE like VSCode. Without significantly rewriting tests and while preserving the use of SafeTestsets, move our test suite to be based around TestItems.jl.

Required skills: Understanding of the julia test runner infrastructure.

Reviewer: Stefan Krastanov

Duration: Expected duration of the project (except potential review overhead)

Payout procedure:

The Funding for these bounties comes from the National Science Foundation and from the NSF Center for Quantum Networks. The payouts are managed by the NumFOCUS foundation and processed in bulk once every two months. If you live in a country in which NumFOCUS can make payments, you can participate in this bounty program.

Click here for more details about the bug bounty program.

Project: "Tensor Networks Backend" [$400]

One of the main design goals of this library is to provide a symbolic front end for many different numerical representations of quantum states and operations. This is done chiefly through the express API. Currently, we have baseline support for state vectors (an interface to QuantumOptics.jl) and for stabilizer tableaux (an interface to QuantumClifford.jl).

In this project we are pursuing an implementation of a similar symbolic-to-numeric interface for a numerical tensor network representation for many of these states and operators. The majority of the already available symbolic operations and pre-defined objects from this symbolic library should be supported. New "predefined" symbolic objects that are common for tensor network problems should be defined as necessary. The contributor should investigate and defend what would be the best tensor network backend -- ITensor.jl seems like a plausible choice.

Required skills: Familiarity with tensor networks

Reviewer: Stefan Krastanov

Duration: Can be reserved for 2 months and potentially extended

Publication: In the next 2 years we plan to release a paper in a selective journal about this software. Contributing to this issue would deserve a co-authorship status on such a paper (if the contributor so desires)

Payout procedure:

The Funding for these bounties comes from the National Science Foundation and from the NSF Center for Quantum Networks. The payouts are managed by the NumFOCUS foundation and processed in bulk once every two months. If you live in a country in which NumFOCUS can make payments, you can participate in this bounty program.

Click here for more details about the bug bounty program.

The @metadata macro doesn't work when docstring are place inside the struct. PR: QuantumSavory/QuantumSavory.jl#73

julia> express(IdentityOp(X1))
Operator(dim=3x3)
  basis: Fock(cutoff=2)
Eye(3)

julia> express(X1)
Ket(dim=2)
  basis: Spin(1/2)
 0.7071067811865475 + 0.0im
 0.7071067811865475 + 0.0im

I would have expected the basis to be the same in both cases, but it seems IndentityOp is losing some information and defaulting to a Fock basis even when it should not be a Fock basis.

@apkille , any idea what introduced this? It was detected by the QuantumSavory tests, which regrettably we did not run because we were having a breaking release

latexify(dagger(X1)) does not work anymore after #40 due to the changes to dagger

detected by JET (those tests need some polish to be more reliable)

@apkille

A backend for QuantumCumulants.jl [$200]

The QuantumCumulants library (part of the QuantumOptics organization) provides for an elegant way to solve truncated differential equations for expectation values of quantum observables. To claim this bounty you need to create an express interface for converting symbolic objects from QuantumSymbolics into objects QuantumCumulants can work with.

Required skills: Knowledge of the QuantumCumulants library

Reviewer: Stefan Krastanov and/or @david-pl

Duration: 2 months

Payout procedure:

The Funding for these bounties comes from the National Science Foundation and from the NSF Center for Quantum Networks. The payouts are managed by the NumFOCUS foundation and processed in bulk once every two months. If you live in a country in which NumFOCUS can make payments, you can participate in this bounty program.

Click here for more details about the bug bounty program.

Project: Aqua static analysis [$200]

We run Aqua.jl static analysis during CI for this library, but currently, we have disabled the piracy and ambiguity checks, as they raise too many errors. This bounty is awarded for fixing these issues and enabling these checks. The bounty might require upstreaming some work from here into QuantumInterface.jl or other packages.

Required skills: Generic Julia skills.

Reviewer: Stefan Krastanov

Duration: 1 month

Payout procedure:

The Funding for these bounties comes from the National Science Foundation and from the NSF Center for Quantum Networks. The payouts are managed by the NumFOCUS foundation and processed in bulk once every two months. If you live in a country in which NumFOCUS can make payments, you can participate in this bounty program.

Click here for more details about the bug bounty program.

Rules_single_qubit.txt

Describe the bug 🐞

The macro @withmetadata adds a metadata property to a defined struct. This becomes an issue when propsequal is called because this function evaluates equality of two symbolic objects by evaluating the equality of their properties. But we shouldn't care about metadata when evaluating equality, as that only contains information about the cached results from express.

Minimal Reproducible Example 👇

julia> state1 = XBasisState(1, SpinBasis(1//2))
|X₁⟩

julia> state2 = XBasisState(1, SpinBasis(1//2))
|X₁⟩

julia> isequal(state1, state2)
false

julia> QuantumSymbolics.propsequal(state1, state2)
false

julia> i1, b1, m1 = propertynames(state1)
(:idx, :basis, :metadata)

julia> i2, b2, m2 = propertynames(state2)
(:idx, :basis, :metadata)

julia> isequal(getproperty(state1, m1), getproperty(state2, m2))
false