Quantum Computing Research

This page is my scrapbook on Quantum Computing. Just random interesting links, sessions and more around Quantum Computing. After others asked me to share the list, I decided to create a public page. Don’t critique the layout, I will get around to correctly attributing and notating content … eventually! May you find this a useful resource.


Forest – Easy, hybrid quantum programing

Presenters: W. Zeng, C. Osborn
Rigetti’s view of the QC world (from Quantum Information Processing 2018) gives a view of coding for QC from emulation to programming.

Forest – Easy, hybrid quantum programming

The Quantum Space Race

Presenters: Steve Martinis, Google

The Quantum Space Race

Unsupervised Machine Learning on a Hybrid Quantum Computer

December 2017
Machine learning techniques have led to broad adoption of a statistical model of computing. The statistical distributions natively available on quantum processors are a superset of those available classically. Harnessing this attribute has the potential to accelerate or otherwise improve machine learning relative to purely classical performance. A key challenge toward that goal is learning to hybridize classical computing resources and traditional learning techniques with the emerging capabilities of general purpose quantum processors. Here, we demonstrate such hybridization by training a 19-qubit gate model processor to solve a clustering problem, a foundational challenge in unsupervised learning. We use the quantum approximate optimization algorithm in conjunction with a gradient-free Bayesian optimization to train the quantum machine. This quantum/classical hybrid algorithm shows robustness to realistic noise, and we find evidence that classical optimization can be used to train around both coherent and incoherent imperfections.



QPU – like a CPU but Quantum

Qubit – like a bit but quantum (and thus significantly more powerful than classical bits as you combine multiple qubits.)

Annealing – Quantum annealing (QA) is a metaheuristic for finding the global minimum of a given objective function over a given set of candidate solutions (candidate states), by a process using quantum fluctuations. (Yep, I am not fully understanding this one yet. Try this. Imagine a series of hills and valleys that you are looking at from the side in a 2D view. To see/read a point in successive valleys in classical computing, you would need to travel up and over the hill in between each one. In annealing, you can cut straight through the mountains to see/read the lowest valley immediately. Did that help? That’s not how it really works but it is sort of how it works.)

Gates – think transistors in a microchip, the basis for logic and processing. Each gate introduces noise, and once the noise reaches a certain level, the QUBITs are unreliable (decoherence) and the quantum superposition state must be recreated for further processing. (Noise and number of gates are probably metrics AppDynamics will need to report if we ever build a QC agent)

Hadamard (H) gate – one-qubit version of the quantum fourier transform

Quantum Noise – see gates. This is the wear on a qubit that comes from reading it.

Superposition – the ability for a qubit to be both ‘0’ and ‘1’ simultaneously for processing (until actually read)

Entanglement (Bell’s theorem refers to it as ‘non local’ connection) – once two qubits are entangled, they can be separated physically and somehow maintain a consistent state over long distances (this is the sort of stuff Einstein called ‘spooky action’ – so there’s that!)

Quantum supremacy – a future moment when quantum devices (without error correction) can perform a well-defined computational task beyond the capabilities of supercomputers

qRAM – In qRAM, 40 qubits can store the same information as 1,000,000,000,000 legacy bits (that is 1012)

Hilbert Space – a mathematical concept that is now an indispensable tool in quantum mechanics. The maths of QC occurs inside the Hilbert space.

Variational circuits – define a set of classical routines which reference within their algorithm quantum circuits

Noisy intermediate-scale quantum computers (NISQ) – the name for the current state of the art QC’s – which is prototype-level and including error correction for up to 10 qubits

Quantum Approximate Optimization Algorithm (QAOA) – ?


Hamiltonian – In quantum mechanics, a Hamiltonian is an operator corresponding to the sum of the kinetic energies plus the potential energies for all the particles in the system. Its spectrum is the set of possible outcomes when one measures the total energy of a system. Because of its close relation to the time-evolution of a system, it is of fundamental importance in most formulations of quantum theory. https://en.wikipedia.org/wiki/Hamiltonian_(quantum_mechanics) https://en.wikipedia.org/wiki/Hamiltonian_mechanics

Adiabatic – https://en.wikipedia.org/wiki/Adiabatic_theorem

Eigenstate – An eigenstate is the measured state of some object possessing quantifiable characteristics such as position, momentum, etc. The state being measured and described must be observable, and must have a definite value, called an eigenvalue. https://en.wikipedia.org/wiki/Introduction_to_eigenstates