quantum-computing

Several katas could have better error messaging:

• Superposition : the test harness could log the actual state of the system after prep vs the expected state before asserting that they are the same (the change would add state prep and logging using DumpMachine to AssertEqualOnZeroState)
• BasicGates : a similar improvement, but a bit more extra code to write a unified test wrapper

Here are some examples:

• Root README is missing machine learning category of samples
• README in algorithms is missing repeat-until-success and sudoku-grover
• [README in diagnostics](https://github.com/microsoft/Quantum/blob/main/samples/diagnostics/RE

Environment

• Qiskit Terra version: 0.20.1
• Python version: 3.10.4
• Operating system: Linux version 5.17.5

What is happening?

When iterating over a Statevector in a foor loop, data is attempted to be accessed after the last element.

How can we reproduce the issue?

import qiskit as qk
sv = qk.quantum_info.states.statevector.Statevector([1,2

Is your feature request related to a use case or problem? Please describe.
Right now a lot of modules (in particular tests) are pretty free form with how they do imports. It's a good practice to import modules wherever possible.

bad:

from cirq.devices import GridQubit

good:

from cirq import devices

devices.GridQubit(whatever)

**Describe the soluti

Context

We would like to define a new operation called IsingXY, as defined in the PennyLane-Braket plugin.

Steps to take

Adding the operation

• Adding the IsingXY class and its attributes to pennylane/ops/qubit/parametric_ops.py.
• Complete its doc

To get this codebase up to standard, we need to add type hints. At the very least, perhaps we should start insisting that all new code has type hints added, but moreover we need to add typing to the code that currently exists.

This is a pretty large project, but luckily it can be done incrementally - I believe at this point it's a stretch goal for v1, if anyone wants to help it would be much ap

Describe the Issue!

Most of the functions in random_objects.py take an N input and an optional dims. Those input are redundant as the size (N) can be obtained from the dims. However the way they handle this inconsistent:

• Many functions, such as rand_super, rand_dm, check that the dims matches the size and raise an error if it doesn't.
• rand_dm_ginibre, rand_super_bcsz j

What is the expected enhancement?

The openQASM project should have release notes associated with each tagged release (see #321). These should contain a summary of all changes included in the prepared release (or the development branch). For ease (and distribution) of maintenance, we should consider using reno which has been used with success in Qiski

Describe the Issue

1. In section 2.4.3 on Controlled Rotations, the line "A controlled R_x(θ) could similarly be made using CNOT gates." seems incorrect.
2. I assume that the line claims that replacing R_y(θ/2) by R_x(θ/2) (similarly for the -θ case), in the circuit above, we would get a controlled R_x(θ). This is incorrect.
3. Passing |1> through q_0, we get X R_x(-θ/2) X R_x(θ/2)q_1, fo

Is your feature request related to a problem? Please describe.
Adding concrete examples to API documentation comments can help clarify how Q# functions and operations are to be used. For example, the documentation for Microsoft.Quantum.Arrays.ElementsAt lists how the function acts on a variety of arrays:

right now, absolute jumps are conflated in the label object here. I'd prefer we instead introduce a new object called absolute-program-location or something like that. (I don't want to use "address" only because it feels too dishonest.) If we do this, then we'd change patch-labels to not overwrite these label objects, and we'