Displaced torontonian sampling time increase about thewalrus HOT 11 CLOSED

Hi @amanuelanteneh, thanks for reporting this.
Can you please post the output of running: import thewalrus; thewalrus.about() ?

Also, if you can post your full code it will make it easier to see if we can reproduce your problem.

from thewalrus.

Hi @CatalinaAlbornoz,
Here is the output of thewalrus.about():

The Walrus: a Python library for for the calculation of hafnians, Hermite polynomials, and Gaussian boson sampling.
Copyright 2018-2021 Xanadu Quantum Technologies Inc.

Python version:            3.8.8
Platform info:             Linux-3.10.0-1127.19.1.el7.x86_64-x86_64-with-glibc2.10
Installation path:         /home/ph/.local/lib/python3.8/site-packages/thewalrus
The Walrus version:        0.19.0
Numpy version:             1.19.2
Scipy version:             1.5.2
SymPy version:             1.6.2
Numba version:             0.51.2

This is the full function that i use to generate the samples and the only place I use functions from the walrus:

def generateSamples(adjMatrix, numSamples, meanN, displacement, maxPhotons):
  modes = adjMatrix.shape[0]

  A = adjMatrix
  Q = gen_Qmat_from_graph(A, meanN)
  V = Covmat(Q, hbar=2) #the covaraince matrix of the pure gaussian state 
  d = np.full( shape=(2*modes), fill_value=displacement, dtype=np.float64 ) 
  samples = torontonian_sample_state(cov=V, mu=d, samples=numSamples, max_photons=maxPhotons)

  return(samples)

It takes in the adjacency matrix of a graph and uses functions from the walrus to embed the matrix into a GBS device which i then sample from. I call this function multiple times for a dataset of graphs. The function seems to run in the expected amount of time when displacement equals 0 but for displacements of 0.1 and 0.25 on each mode the runtime increases very drastically (from about 8 hours to over 7 days) which i don't believe should be the case.

from thewalrus.

Thank you @amanuelanteneh. We will take a look into this.

from thewalrus.

@CatalinaAlbornoz Thanks! It might also be that this isn't how the displacement is meant to be specified however I can't find any example code on how to sample from a displaced Gaussian state using thewalrus so I'm unsure.

from thewalrus.

The slowdown should only be 2x. How many modes are you working with?

from thewalrus.

@ziofil on average the number of nodes in the graphs I'm looking at is about 25 so around 50 modes on average.

from thewalrus.

Those are a lot of modes... I'm wondering if the slowdown is due to other effects (like memory swapping and so on). Could you try with fewer modes and see if the slowdown is the same?

from thewalrus.

also, how sparse is your adjacency matrix?

from thewalrus.

The adjacency matrices range in sparsity but the majority seem fairly sparse.

from thewalrus.

Thank you @amanuelanteneh. Does having fewer modes give you the same slowdown? Or do you have the same slowdown with fewer modes?

from thewalrus.

Hello, I've been running some more simulations and it appears that the issue is no longer a problem. Sorry for the delay in response.

from thewalrus.