Author: jarrodmcc

Basic quantum circuit simulation in Python

I’ve always been a proponent of the idea that one of the best ways to learn about a topic is to code up a simple example that uses that idea/concept/algorithm.  In conversations I’ve had with students recently, I’ve realized there

VQE, Excited States, and Quantum Error Suppression

It’s been some time since our original hybrid quantum-classical algorithm, the variational quantum eigensolver (VQE), made its debut on a photonic quantum device.  Since that time there have been many developments, some of which I outlined in a previous post

A quick molecule in Processing.js and Python

As an extension to my last post on rendering Processing code in an IPython notebook, I thought it might be fun to play a bit with the 3D functionality and see how easy it would be to build an extremely

Processing.js in an IPython Notebook

I’ve been playing a bit with generative art recently, and in this domain the Processing language is a popular choice.  Processing allows fairly seamless creation of both 2D and 3D images as well as natural interactivity.  I had some interest

Simple bash-parallel commands in python

One of the benefits of using a primitive system like collections of flat files for data storage is the ability to trivially do work in parallel on them through the shell.  This seems to be a relatively common workflow in

Integrating over the unitary group

Quantifying the volumes of different types of quantum states with respect to each other is an interesting tool for analysis that I’ve recently become interested in.  For example, did you know the volume of separable states is super-doubly-exponentially small with

Expressive power, deep learning, and tensors

Tensors are kind of like the wild west of applied math these days.  They are a brave new territory and somewhat dangerous with regards to procedures one might borrow from matrices. In particular, “Most tensor problems are NP-Hard”.  Despite this

A new paper on the VQE

Quantum computers are a big interest of mine, and in particular I think there’s a lot to be learned in using prototype devices available in the lab today. Unfortunately, a lot of the algorithms we talk about today are simply

Distance is weird in many-particle quantum mechanics

Distance measures between quantum states are interesting for all kinds of reasons.  I’ve been thinking about them a lot lately as they pertain to machine learning in and around quantum mechanics, as well as just generic approaches to studying many-body