Skip to main content

This package was made to perform continous time quantum random walks on domain-specific networks

Project description

QuantumRandomWalk package

This package was built as the final summary assignment for the University of Rhode Island Quantum Computinhg Graduate Certificate by Jose Hernandez. The original project utilized quantum random walks to calculate probability of visit per node with a start node x or probability of edge existence between all possible pair nodes.

The purpose of this package is to allow network scientists to programmatically apply continous time quantum random walks on their own networks without needing signficant quantum preparation or onboarding.m This is alos meant as a begginer-friendly introductionn to quantu circuits which is why every effort has been made to simplify parameters and inputs as much as possible.

Capabilities:

Included Capabilities:

  1. Quantum walk from a single start node evolving outward (e^{-iAt}).
  2. Quantum walk from a single start node evolving inward (e^{iAt}).
  3. Quantum walk from a superposition of all nodes.

Planned Capabilities:

  1. Pre-processing for specific network formats such as Gephi-csv exports
  2. Post-processing utilities for extracting summary statistics and analyzing distributions.

Assumptions:

NOTE: A preprocessing module will be added before first major release to complete this preprocessing automatically for any network

  • The adjacency matrix should be square of size 2^n × 2^n.
  • Nodes are indexed from 0 to 2^n - 1 and correspond to binary quantum states.
  • If your graph doesn't fit this format, preprocessing will be needed.

Content:

Classes:

  • QuantumRandomWalk: Encapsulates circuit setup, walk simulation (inward or outward), and measurement.
  • ResultsDataFrame: Encapsulates all post-processing functions for the dataframe

Functions:

  • perform_one_node_walk: Performs a continuous-time quantum walk from a specific start node over time steps.
  • perform_superpositioned_walk: Performs a continous-time quantum walk starting at a superposition of all nodes

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quantumrandomwalks-0.0.3.tar.gz (7.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

quantumrandomwalks-0.0.3-py3-none-any.whl (8.1 kB view details)

Uploaded Python 3

File details

Details for the file quantumrandomwalks-0.0.3.tar.gz.

File metadata

  • Download URL: quantumrandomwalks-0.0.3.tar.gz
  • Upload date:
  • Size: 7.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for quantumrandomwalks-0.0.3.tar.gz
Algorithm Hash digest
SHA256 003cee867536cbc50e999d1c3f7f49e7dfd283b10656eb140cd9a152473d0014
MD5 74ab80b70885e64f48fa9ce6b3f6f5f7
BLAKE2b-256 ae423656d2094ac5f924f761cd494ab939ba1374122593191c55d5ea895db36c

See more details on using hashes here.

File details

Details for the file quantumrandomwalks-0.0.3-py3-none-any.whl.

File metadata

File hashes

Hashes for quantumrandomwalks-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 aee56b706eccda98afe5d8f1b84debd8d5cb6f480c590eef926ffd35d16a407d
MD5 e8d346a5c998a4456a58c0a3d25fa2ce
BLAKE2b-256 380760305001803c160e28f8b6c9df98871fe8b923af5de215b785f53d63def3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page