Quantum Bayesian Networks

February 2, 2016

First Major Commit to Quantum Fog in Python

Filed under: Uncategorized — rrtucci @ 4:56 pm

Today is Groundhog day, Feb. 2, 2016. This holiday holds special significance in Quantum Computing History. Indeed, on another Groundhog day in the distant past, in the year 2015, a watershed historic quantum event occurred, namely Jimmy the Groundhog bit Seth Lloyd’s ear.

Other quantum watershed events have occurred since them, like, for example, Caltech held its “One Entangled Evening” and Alex Winter screened his NSF funded 10 minute mini-movie “Anyone can Quantum”. But those events are California/Hollywood glitzy, whereas groundhog day is a more folksy affair (old white men with funny top hats bugging a chubby rodent who just wants to go back to sleep).

artiste-logo Since we here at artiste-qb.net are more folksy than glitzy, we decided to celebrate this holiday by releasing today our first version of Quantum Fog in Python (QFog is open sourced under the BSD license, and it is available at GitHub)

Basically, what I did was to refurbish an old open-source program called PBNT by Elliot Cohen. PBNT does classical Bayesian Networks using 3 inference algorithms: Enumeration (brute force), MCMC and Join Tree (aka Junction Tree).

The join tree algo used by PBMT and QFog is the one described in the following very detailed and clear, cookbook paper: _Inference in Belief Networks, A Procedural Guide_, by C Huang and A. Darwiche (1996)

Our new QFog release does BOTH, classical and quantum Bnets using the same 3 algos. One of our eventual goals is to write a quantum computer programming language based on quantum Bnets.


1 Comment »

  1. Great work running with PBNT and cleaning it up to make for a awesome Quantum Fog reboot!

    Comment by Quax — February 2, 2016 @ 11:45 pm

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