Simulating Sycamore quantum circuits classically using tensor network algorithm.

Overview

Simulating the Sycamore quantum supremacy circuit

This repo contains data we have obtained in simulating the Sycamore quantum supremacy circuits with $n=53$ qubits, $m=20$ cycles using the tensor network method proposed in arXiv:2103.03074.

We plan to release the code soon.

Explanation of data

  1. data/circuit_n53_m20_s0_e0_pABCDCDAB.py is the circuit file which has been download from the Google's data repository for the Sycamore circuits.
  2. data/bipartition_n53_m20_s0_ABCD_s24_simplify_.txt is the initial bipartition of the simplified tensor network corresponding to Sycamore circuit with 53 qubits, 20 cycles, seed 0, elide 0 and ABCDCDAB sequence. There are two lines in the file, the first line indicates the tail partition which includes 21 open qubits, while the second line includes the head partition with 32 closed qubits. The simplification of the tensor network is done by sequentially contracting tensors with 2 or less dimensions.
  3. data/n53_m20_s0_ABCD_s24_simplify_gpulimit_30_edges.txt contains the 23 slicing edges which splits the overall contraction task into $2^{23}$ subtasks, each of which has space complexity $2^{30}$ hence can be contracted using fit into 32G memory.
  4. data/n53_m20_s0_ABCD_s24_simplify_gpulimit_30_ordernew.txt includes the contraction order. For each edge in the contraction order, say $i, j$, the $i$th and $j$th tensor in the head partition will be contracted by tracing out the shared indices. Then the resulting tensor will be put back into the $i$th position.
  5. vector.pt contains the cut tensor of of the head partition whose overall dimension is $2^{23}$ and the annotations of corresponding dimensions. The file is saved using pytorch, one can use torch.load to load the data.
  6. The obtained $2^{21}$ samples for the Sycamore circuits with $n=53$ qubits and $m=20$ cycles and their probabilities and amplitudes are listed in probs.txt file. Notice that the configuration we assigned to all closed qubits are fixed to $\underbrace{0,0,0,\cdots,0}_{32}$, and the open qubit ids are 11, 12, 13, 19, 20, 21, 22, 23, 28, 29, 30, 31, 32, 37, 38, 39, 40, 41, 44, 45, 46.

Notice

We noticed that in our paper arXiv:2103.03074 we have a misprint in the first row of Tab.III, where the amplitude should be |amplitude|. Neverthless, we put the refined table below.

image-20210308101302534

The $2^{21}$ bitstrings with amplitudes and probabilities can be download here.

Owner
Feng Pan
PHD candidate on theoretical physics. Personal interest in learning theory by statistical physics approaches.
Feng Pan
GuideDog is an AI/ML-based mobile app designed to assist the lives of the visually impaired, 100% voice-controlled

Guidedog Authors: Kyuhee Jo, Steven Gunarso, Jacky Wang, Raghav Sharma GuideDog is an AI/ML-based mobile app designed to assist the lives of the visua

Kyuhee Jo 5 Nov 24, 2021
Shallow Convolutional Neural Networks for Human Activity Recognition using Wearable Sensors

-IEEE-TIM-2021-1-Shallow-CNN-for-HAR [IEEE TIM 2021-1] Shallow Convolutional Neural Networks for Human Activity Recognition using Wearable Sensors All

Wenbo Huang 1 May 17, 2022
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

CycleGAN PyTorch | project page | paper Torch implementation for learning an image-to-image translation (i.e. pix2pix) without input-output pairs, for

Jun-Yan Zhu 11.5k Dec 30, 2022
TensorFlow 2 AI/ML library wrapper for openFrameworks

ofxTensorFlow2 This is an openFrameworks addon for the TensorFlow 2 ML (Machine Learning) library

Center for Art and Media Karlsruhe 96 Dec 31, 2022
Leveraging Social Influence based on Users Activity Centers for Point-of-Interest Recommendation

SUCP Leveraging Social Influence based on Users Activity Centers for Point-of-Interest Recommendation () Direct Friends (i.e., users who follow each o

Kosar 8 Nov 26, 2022
Spline is a tool that is capable of running locally as well as part of well known pipelines like Jenkins (Jenkinsfile), Travis CI (.travis.yml) or similar ones.

Welcome to spline - the pipeline tool Important note: Since change in my job I didn't had the chance to continue on this project. My main new project

Thomas Lehmann 29 Aug 22, 2022
MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice

Sampyl May 29, 2018: version 0.3 Sampyl is a package for sampling from probability distributions using MCMC methods. Similar to PyMC3 using theano to

Mat Leonard 304 Dec 25, 2022
Visual odometry package based on hardware-accelerated NVIDIA Elbrus library with world class quality and performance.

Isaac ROS Visual Odometry This repository provides a ROS2 package that estimates stereo visual inertial odometry using the Isaac Elbrus GPU-accelerate

NVIDIA Isaac ROS 343 Jan 03, 2023
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place

Mikaela Uy 294 Dec 12, 2022
Starter Code for VALUE benchmark

StarterCode for VALUE Benchmark This is the starter code for VALUE Benchmark [website], [paper]. This repository currently supports all baseline model

VALUE Benchmark 73 Dec 09, 2022
This repository is the code of the paper "Sparse Spatial Transformers for Few-Shot Learning".

🌟 Sparse Spatial Transformers for Few-Shot Learning This code implements the Sparse Spatial Transformers for Few-Shot Learning(SSFormers). Our code i

chx_nju 38 Dec 13, 2022
Official implementation of "Dynamic Anchor Learning for Arbitrary-Oriented Object Detection" (AAAI2021).

DAL This project hosts the official implementation for our AAAI 2021 paper: Dynamic Anchor Learning for Arbitrary-Oriented Object Detection [arxiv] [c

ming71 215 Nov 28, 2022
Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts

t5-japanese Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts. The following is a list of models that

Kimio Kuramitsu 1 Dec 13, 2021
PyElecCL - Electron Monte Carlo Second Checks

PyElecCL Python program to perform second checks for electron Monte Carlo radiat

Reese Haywood 3 Feb 22, 2022
Pytorch version of VidLanKD: Improving Language Understanding viaVideo-Distilled Knowledge Transfer

VidLanKD Implementation of VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer by Zineng Tang, Jaemin Cho, Hao Tan, Mohi

Zineng Tang 54 Dec 20, 2022
SplineConv implementation for Paddle.

SplineConv implementation for Paddle This module implements the SplineConv operators from Matthias Fey, Jan Eric Lenssen, Frank Weichert, Heinrich Mül

北海若 3 Dec 29, 2021
Official TensorFlow code for the forthcoming paper

~ Efficient-CapsNet ~ Are you tired of over inflated and overused convolutional neural networks? You're right! It's time for CAPSULES :)

Vittorio Mazzia 203 Jan 08, 2023
Canonical Capsules: Unsupervised Capsules in Canonical Pose (NeurIPS 2021)

Canonical Capsules: Unsupervised Capsules in Canonical Pose (NeurIPS 2021) Introduction This is the official repository for the PyTorch implementation

165 Dec 07, 2022
AutoDeeplab / auto-deeplab / AutoML for semantic segmentation, implemented in Pytorch

AutoML for Image Semantic Segmentation Currently this repo contains the only working open-source implementation of Auto-Deeplab which, by the way out-

AI Necromancer 299 Dec 17, 2022
FB-tCNN for SSVEP Recognition

FB-tCNN for SSVEP Recognition Here are the codes of the tCNN and FB-tCNN in the paper "Filter Bank Convolutional Neural Network for Short Time-Window

Wenlong Ding 12 Dec 14, 2022