Quantum Class 20, Mon 2022-11-21
1 Final project presentations
Presentations will be the last 3 classes: Dec 1, 5, 8. FCFS. Max 6 groups per day.
Pick your date here: https://doodle.com/meeting/participate/id/egZG5Pjd
When signing up, use enough of your name(s) that I can recognize you.
2 NVIDIA Quantum Computing, 2
NVIDIA (and other companies) sees a growth area in providing QODA, a layer of services on top of the quantum computing HW. The goal is to make that easier to use and more portable.
The analogy is that CUDA hides some of the GPU complexity.
QODA also permits various backends: simulators and eventually real HW.
Nice intro: https://docs.nvidia.com/cuda/cuquantum/overview.html
NVIDIA Special Address at Q2B: Defining the Quantum Accelerated Supercomputing Platform 18:39. Jul 12, 2022
Quantum computing has the potential to offer giant leaps in computational capabilities, impacting a range of industries from drug discovery to portfolio optimization. Realizing these benefits requires pushing the boundaries of quantum information science in the development of algorithms, research into more capable quantum processors, and the creation of tightly integrated quantum-classical systems and tools. We'll review these challenges facing #quantumcomputing, showcase how #GPUcomputing can help, and reveal exciting developments in tightly integrated quantum-classical computing. https://developer.nvidia.com/qoda
Watch Nvidia Reveal Quantum Computing Platform, QODA 6:53 Jul 12, 2022
At Q2B, Nvidia announces QODA, a new hybrid quantum-classical computing platform. See it explained here.
Q2B 2021 | Accelerating Quantum Algorithm Research with cuQuantum | Harun Bayraktar 29:52. December 9, 2021. Excellent solid talk.
I tried to get QODA running to show the class.
However it is still a work in progress.
You can (try to )install QODA from https://docs.nvidia.com/cuda/cuquantum/custatevec/getting_started.html
The deb fails on my machine running Ubuntu 22.10 because of a cublas version clash.
The tarball installs.
Compiling fails because it doesn't support the latest g++.
-allow-unsupported-compiler seems to override that.
Several programs are supplied but all the programs just say 'passed' when executed.
3 Classiq - Quantum algorithm design platform
Here's another company working on the layers above the HW.
"Classiq is revolutionizing the process of developing quantum computing software.
"Our platform helps you build complex, optimized and hardware-aware quantum circuits and algorithms that could not be created otherwise. "
https://www.classiq.io/ Watch the short video.
They use the Variational Quantum Eigensolver (VQE) as an example.
4 Variational Quantum Eigensolver (VQE)
This is a big current class of applications for hybrid classic - quantum computers.
I think it's not quite practical yet, but it's close.
Say you want to know the lowest energy state of a molecule.
It's the lowest eigenvalue of a Hamiltonian.
However the Hamiltonian cannot be calculated explicitly but must be simulated.
This is very expensive, but less so on a quantum computer (because it uses quantum physics).
It depends on some parameters.
Use a classical computer to run an optimization search on the parameters, calling a quantum computer to evaluate the function (the Hamiltonian).
https://qiskit.org/textbook/ch-applications/vqe-molecules.html very good.
24. Variational quantum eigensolver (VQE) 19:12, Dec 18, 2020, Jochen Rau. very good.
Variational Quantum Eigensolver (VQE) | PennyLane Tutorial 17:44
VQE Zero to Hero 20:50 May 9, 2022
"The Variational Quantum Eigensolver (VQE) is one of the most promising algorithms for near term quantum hardware, but how does it work? Rensselaer Polytechnic Institute student Owen Lockwood shows you how to get from the basics of quantum mechanics and the Schrödinger equation to the second quantized electronic hamiltonian and how this forms the basis of the VQE."
Goes into the physics and chemistry.
5 My predictions for the winners
If I had to pick a HW winner, I'd pick Intel. However it's early still.
For the SW, perhaps NVIDIA, or Intel, Amazon, Microsoft.
Dunno about the Itty Bitty Machine company. Their best product IMO is their Power architecture as used with NVIDIA in supercomputers.