I am interested in simulating quantum many body systems in condensed matter physics and quantum chemistry.
Working on PennyLane - a cross-platform Python library for differentiable programming of quantum computers.
Recent blog posts:
- Learning shallow quantum circuits with local inversions and circuit sewing
Shocasing circuit sewing with local inversions that have been introduced in introduced 2401.10095. - Evaluating analytic gradients of pulse programs on quantum computers
TLDR of our paper 2309.16756 on a new method to evaluate gradients of quantum pulse programs on quantum hardware. - Pulse programming on OQC Lucy in PennyLane
You can now run pulse programs on OQC's Lucy quantum computer in PennyLane via AWS Braket. Also discussing some basic physics of driving transmon qubits. - Is quantum computing useful before fault tolerance?
Reproducing the key ingredients of the zero noise extraplation in IBM's paper on utility of quantum computing Nature 618, 500–505, 2023 and a comment on the comparison with classical methods. - Differentiable pulse programming with qubits in PennyLane
Introducing pulse programming, that is, manipulating quantum states via the Hamiltonian interactions on the hardware level, and optimizing pulse shapes for variational quantum algorithms. - Differentiating quantum error mitigation transforms
Differentiating through error mitigation transforms and proposing to differentiate (hyper) parameters of the transform itself. - Estimating observables with classical shadows in the Pauli basis
Unraveling some of mysteries about classical shadows. - Generalization in QML from few training data
Reproducing the results of 2111.05292
PhD Thesis: Investigating Quantum Many-Body Systems with Tensor Networks, Machine Learning and Quantum Computers