Blueqat

Release Date
Mar. 2, 2021

Enhancement
- Make mat1 gate and basic transpiler. It will facilitate circuit optimizations and execution on the real quantum machine
- Add ZZ gate, this is for trapped-ion based machine's basis gate
- Update for next version of qgate (thank you, Morino san!)

Debug
- CCZ gate was not available. Now, it is available.

Release Date
Aug. 13, 2020

Enhancement
- Add `reset` operation. This is equivalent with measurement without recording measured result and apply X gate when 1 is measured.

Debug
- Correct numba's global phase error.

API Change
- `opt` module is renamed to `wq`.

Greater than 1: v0.3.17 is faster than v0.3.16
Less than 1: v 0.3.17 is slower than v0.3.16


For large Hamiltonian, this release is 100 times faster than previous release

LiH Hamiltonian
Compared with OpenFermion's `qubit_operator_sparse`.
Normally, the number of qubits is 12, but can be add redundant qubit via n_qubits parameter.
Measure 12 qubits to 19 qubits.

(*1): Due to lack of memory, so many swap out occurred. Blueqat implementation is less memory consumption than OpenFermion.

How to install
New install
`pip install blueqat`

Update
`pip install -U blueqat`

This is hotfix of [0.3.15](https://github.com/Blueqat/Blueqat/releases/tag/0.3.15) bug.
Sorry for inconvenient.

Changes
`Vqe()` class
When sampler is default, make sparse matrix and calculate expectation directly.
This is for performance improvement.
(If you're using default sampler, your VQE code is speed-up without any changes.)

VQE is still under refactoring process and this API may be changed in future release, however, because this feature is very important, I want to merge this feature in the master.

Many cases of VQEs, this change makes fantastic speed-ups.
However, some cases, this change makes slow down.

To make previous default behaviour, specify sampler as previous default sampler.

py
from blueqat.vqe import Vqe, non_sampling_sampler
hamiltonian = ...
Vqe(hamiltonian, sampler=non_sampling_sampler)


`pauli.to_matrix()` qubit order is reordered.
Previous: X[0] * Y[1] is X ⊗ Y
New: X[0] * Y[1] is Y ⊗ X

New behavior is equivalent with Blueqat circuit's statevector order.

This version contains critical bug. Please use [0.3.16](https://github.com/Blueqat/Blueqat/releases/tag/0.3.16) or later version.

Changes
`Vqe()` class
When sampler is default, make sparse matrix and calculate expectation directly.
This is for performance improvement.
(If you're using default sampler, your VQE code is speed-up without any changes.)

VQE is still under refactoring process and this API may be changed in future release, however, because this feature is very important, I want to merge this feature in the master.

Many cases of VQEs, this change makes fantastic speed-ups.
However, some cases, this change makes slow down.

To make previous default behaviour, specify sampler as previous default sampler.

py
from blueqat.vqe import Vqe, non_sampling_sampler
hamiltonian = ...
Vqe(hamiltonian, sampler=non_sampling_sampler)

Release Date: 12 May. 2020

Features
- Add new gates, rxx, ryy, rzz, cswap.
- Add `Circuit.dagger`. `Circuit().rx(0.1)[0].cx[0, 1].t[0].dagger()` is `Circuit().tdg[0].cx[0, 1].rx(-0.1)[0]`.
- Add `mixer` argument for QaoaAnsatz. (This feature may be changed in the future.) This is for Quantum Alternative Operator Ansatz.
- Add `sparse` option for `pauli.Expr.to_unitary`. It returns scipy's sparse matrix. `(X[0] + Y[3]).to_matrix(sparse='csc') csc matrix` The performance for larger qubits expr is better than (default's) dense matrix, but still not fast.

Experimental
Add `blueqat.experimental.utils.circuit_to_unitary`. It returns unitary matrix instead of statevector.
Blueqat already has to_unitary method for sympy's unitary gate.
However, this function runs the circuit with a backend which returns statevector.
This feature is useful for debugging the circuit, and it's too heavy for larger circuit.

Install
New install
`pip install blueqat`

Update
`pip install -U blueqat`