Quantum Chemical Simulation: Molecules on Qubits
How molecules are simulated on qubits: mapping electrons to qubits, algorithms such as VQE, and uses in materials, catalysts and drugs.
How molecules are simulated on qubits: mapping electrons to qubits, algorithms such as VQE, and uses in materials, catalysts and drugs.
The main kinds of quantum speedup: exponential, polynomial, provable and heuristic, with Shor’s and Grover’s algorithms as examples.
Which quantum chemistry simulations run today, classical methods such as Hartree-Fock and DFT, and where quantum computers might add value.
Photonic quantum computing uses photons as qubits. How photons encode information, uses in cryptography and the challenges of scaling up.
Rydberg atoms have highly excited electrons that interact strongly over micrometers. How this enables fast two-qubit gates in atom arrays.
Donor-based quantum computing uses single phosphorus or other donor atoms in silicon as qubits. How they are placed, controlled and scaled.
Molecular quantum computing stores qubits in the spins or states of molecules. Principles, possible applications, advantages and challenges.
Solid-state NMR quantum computing encodes qubits in nuclear spins in crystals. Its advantages over liquid NMR, challenges and prospects.
Quantum chemical dynamics follows how molecules move and react in time, including tunneling and energy transfer. Methods and uses.
Which methods are used to run drug discovery problems on quantum hardware, such as VQE and phase estimation, and what they achieve today.
The main quantum cloud platforms compared, including IBM Quantum, Amazon Braket and Azure Quantum: what they offer, costs and limitations.
What quantum annealing can solve: how it works, how it compares with classical optimizers, its hardware and software, and applications.