Wangruby12

Wangruby12's Stars

• Jay-Patel-257/Qhack-2022

  The variational quantum eigensolver (VQE) is generally used for finding the ground state energy of a given hamiltonian. To find the kth excited state energy of the hamiltonian we need to run the VQE optimization process at least k+1 times. Each time we also need to calculate the hamiltonian again, taking into account the state of the previous iteration. Even after that, the accuracy decreases as the value of k increases. The Subspace Search VQE (SSVQE) algorithm is used to find the kth excited-state energy of a hamiltonian in two subsequent optimization processes. Research on a more generalized version of SSVQE, namely Weighted SSVQE, shows that by using the weights as hyperparameters we can find the kth excited-state energy in just a single optimization process. There are two variants of this algorithm: Weighted SSVQE to find kth excited state energy, and weighted SSVQE to find all energies up to the kth excited state.

  Language:Jupyter Notebook53

• beneklins/qiskiteers_h2

  Qiskit routine to find the ground state of H₂ using a variational quantum eigensolver (VQE). Made for the QSciTech-QuantumBC 2021 workshop on gate-based quantum computing.

  Language:Jupyter Notebook1

• Bikramaditya0154/Quantum-simulation-of-excited-states-of-molecular-oxygen-using-VQE-

  Codes of quantum simulation of excited states of molecular oxygen using Variational Quantum Eigensolver. The basis set used is cc-pVDZ.

  Language:Jupyter Notebook1

• CharulataJain/Kagome_VQE

  Preparation of the highly frustrated Ground State of a Kagome Lattice Heisenberg spin ½ Model using the Variational Quantum Eigensolver

  Language:Jupyter Notebook3

• ARaj-007/HeisnenbergSpinModelSimulator

  Calculating the ground state energy of the Heisenberg spin model using a custom made Variational Quantum Eigensolver.

  Language:Jupyter Notebook1

• MiniSean/VQE_ErrorMitigation

  Supervised project that emulates a noisy variational quantum eigensolver. Error mitigation techniques are applied in order to improve performance.

  Language:Python1

• Matt-Salamon/VQE-Ising-model

  Codes and data for a summer project on applying the Variational Quantum Eigensolver algorithm to the transverse-field Ising model.

  Language:Jupyter Notebook2

• leductruyen/Quantum-Computing-Intern-Variatioal-Quantum-Algorithm-

  Basic Variational Quantum Eigensolver (VQE) for Ising Model (Implementation, Ansatz, Cost function, Optimization)

  Language:Jupyter Notebook3

• erinaldi/bmn2-qiskit

  Variational Quantum Eigensolver for matrix quantum mechanics.

  Language:Jupyter Notebook33

• GiggleLiu/QuantumMPS

  Variational Quantum Eigensolver with Fewer Qubits

  Language:Julia257

• e-eight/vqe

  Variational Quantum Eigensolver demonstration (for QOSF 2020 mentorship program)

  Language:Python63

• QuContractor/CVQE

  Quantum snake algorithm: Collective variational quantum eigensolvers for quantum chemistry

  Language:Jupyter Notebook82

• krishphys/LiH_Variational_quantum_eigensolver

  Final Project for Qiskit Global Summer School: Simulating the LiH molecule using Qiskit variational quantum eigensolvers.

  Language:Jupyter Notebook13

• smfarzaneh/vqe-tutorials

  Tutorials for Variational Quantum Eigensolver Algorithm: Theory and Implementation

  Language:Jupyter Notebook31

• Soki-Fuchi/VariationalQuantumEigensolver

  Language:Python1

• walid-mk/VQE

  I Used the Variational Quantum Eigensolver (VQE) to find the ground state of a 4by4 matrix hamiltonian which we will use two qubits for it. The VQE algorithm is run in a noisy and noiseless simulator. The code implementation is written with the Qiskit language.

  Language:Jupyter Notebook135

• kattemolle/HVQE

  User-friendly but high-performance code for simulating Variational Quantum Eigensolvers for the Heisenberg model on any lattice. It is designed to support a computer-cluster workflow.

  Language:Python195