Information loss and run time from practical application of quantum data
  compression
We examine information loss, resource costs, and run time from practical
application of quantum data compression. Compressing quantum data to fewer
qubits enables efficient use of resources, as well as applications for quantum
communication and denoising. In this context, we provide a description of the
quantum and classical components of the hybrid quantum autoencoder algorithm,
implemented using IBM's Qiskit language. Utilizing our own data sets, we encode
bitmap images as quantum superposition states, which correspond to linearly
independent vectors with density matrices of discrete values. We successfully
compress this data with near-lossless compression using simulation, and then
run our algorithm on an IBMQ quantum chip. We describe conditions and run times
for compressing our data on quantum devices.
Saahil Patel Benjamin Collis William Duong Daniel Koch Massimiliano Cutugno Laura Wessing Paul Alsing