[FRIAM] Quantum Computing

[Marcus Daniels]

AQC, and quantum computers in general, are analog computers.    They are good for sampling, but to really find the lowest energies on a complex problem, some classical assist is helpful.

From: Friam <friam-bounces at redfish.com> on behalf of Steven A Smith <sasmyth at swcp.com>
Reply-To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com>
Date: Sunday, January 27, 2019 at 10:32 AM
To: "friam at redfish.com" <friam at redfish.com>
Subject: Re: [FRIAM] Quantum Computing


FWIW, my nephew is in the middle of his PhD in Materials Science in the UofA working on their Phononic Quantum Computing program.    I can't suss out how fast it is moving... he only sees the project through the tiny sliver of his own contribution, but it *seems* to promise much larger PhiBit (Phononic QBit) counts at room temperature, etc.   Some of the underlying engineering is quite fascinating (e.g. modulating the speed of sound in glass rods using coherent light to simulate an exponential "horn").

https://mse.engineering.arizona.edu/news-events/mse-researcher-uses-phononics-build-quantum-computers

I've been trying to wrap my head around the implications of AQC for the kinds of problems I've been using 3D graph layout to try to develop intuition on.   The goal is *rarely* to truly minimize the energy of the system (modeled as a graph with *vectors* of edge-weights rather than simple scalars) to explore the trade-space of the systems being modeled.   In the problem-domain of interest, the challenge is not to find "the answer" but rather to explore the implied landscape of high-dimensional problems.

- Steve
On 1/27/19 9:00 AM, Marcus Daniels wrote:
Jochen writes:

“How do you program a AQC quantum computer? Somehow it must be setup to execute a certain type of calculation?”

An AQC program can be thought of as a graph where the nodes have a value that represents a linear bias up or down for qubit spins in the problem.   Values on edges in the graph represent the tendency of the spins to attract or repel one another.   (The graph is sent to the annealer as a matrix.)   The output is a vector of spins that have a Boltzmann-like distribution given the relative magnitude of the coefficients in the graph to the finite temperature of the machine.    You can find examples on the web of factoring / inverting calculations, social network algorithms, vehicle routing, and a range of other applications.    There are theory papers (Aharonov 2004) that demonstrate that AQC is equivalent to the gate model.

“ And what do you think about photonic quantum computers? The Canadian company Xanadu from Toronto tries to go in this direction.
https://www.xanadu.ai/  “

Another well-known one is IonQ.   One of their founders gave a public lecture in Santa Fe a few months ago.  These are intriguing systems, but they aren’t big enough yet to do meaningful calculations.  Honeywell is getting into that area too.  And there are some smaller start-ups like Atom Computer.

Marcus




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