Comments (3)
royess
commented on May 29, 2024
Besides, I am reproducing QCNN for my research. So I am interested in contributing when I finish it.
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refraction-ray
commented on May 29, 2024
Besides, I am reproducing QCNN for my research. So I am interested in contributing when I finish it.
Great! I can think of two ways to make this contribution. 1. as a template function for qcnn in /tensorcircuit/templates/block.py 2. as a integrated Jupyter tutorial on QCNN in /docs/source/tutorial
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refraction-ray
commented on May 29, 2024
I suddenly realized that tensorcircuit is perfectly suitable for QCNN implementation as the effective depth of QCNN is rather low and thus we can hopefully simulating training QCNN made of a lot of qubitsใ
Reversely, also very suitable for mera type circuit (qubits getting more in time direction, eg see https://arxiv.org/pdf/2210.15053.pdf)
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Related Issues (20)
- docker file need updating HOT 2
- Wired input and output of function "c.amplitude" HOT 3
- Enhance <QAOA portfolio tutorial> HOT 4
- Fermion Gaussian State Simulator HOT 3
- Stabilizer simulator
- Backend agnostic implementation of quantum Hamiltonian generation
- Applying gates with jnp index HOT 7
- Support trainable adptive circuit HOT 2
- Implementation of SHVQE with QAS HOT 1
- tensor network representation of a tensor circuit HOT 2
- Allow sparse matrix as circuit input HOT 3
- AttributeError: module 'tensorflow' has no attribute 'sparse' HOT 2
- Bug in qiskit circuit parsing HOT 2
- jit compile circuit with any gate HOT 2
- `copy` operation of DM circuit forgets previous `apply_general_kraus` operations HOT 1
- MPS circuit with JIT compilation HOT 8
- Sampling from circuit does not give proper bitstring HOT 4
- Add Jittor backend HOT 3
- Stabilizer simulation example utilizing stim backend
- Add examples benchmarking different contractor settings provided by cotengra
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