Quantum Generative Adversarial Networks to Reproduce Calorimeters Outputs

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Quantum Generative Adversarial Networks to Reproduce Calorimeters Outputs 19 May 2021 QGAN to Reproduce

Quantum Generative Adversarial Networks to Reproduce Calorimeters Outputs 19 May 2021 QGAN to Reproduce Calorimeters Outputs Su Yeon Chang, Sofia 1 Vallecorsa

Continuous Variable (CV) Quantum Computing Gate Unitary Displacement Rotation Gaussian Squeezing Beamsplitter Kerr Non-gaussian

Continuous Variable (CV) Quantum Computing Gate Unitary Displacement Rotation Gaussian Squeezing Beamsplitter Kerr Non-gaussian https: //strawberryfields. readthedocs. io/en/stable/introduction. html 19 May 2021 QGAN to Reproduce Calorimeters Outputs 2

CV Quantum Neural Networks Interferometer Squeezing Displacement Non-gaussian Orthogonal Diagonal https: //doi. org/10. 1038/ncomms

CV Quantum Neural Networks Interferometer Squeezing Displacement Non-gaussian Orthogonal Diagonal https: //doi. org/10. 1038/ncomms 13795 19 May 2021 QGAN to Reproduce Calorimeters Outputs 3

CV Quantum GAN Generator https: //arxiv. org/pdf/1811. 04968. pdf Discriminator Update parameters using Quantum

CV Quantum GAN Generator https: //arxiv. org/pdf/1811. 04968. pdf Discriminator Update parameters using Quantum Gradient descent https: //arxiv. org/pdf/1909. 07806. pdf https: //arxiv. org/pdf/1612. 01789. pdf 19 May 2021 QGAN to Reproduce Calorimeters Outputs 4

Implementation 19 May 2021 QGAN to Reproduce Calorimeters Outputs 5

Implementation 19 May 2021 QGAN to Reproduce Calorimeters Outputs 5

Simple classifier test ü Reduce the problem size into 1 dimension and bin into

Simple classifier test ü Reduce the problem size into 1 dimension and bin into 3 pixels → 3 qumodes ü Use CV Neural Network to classify real and fake data (Case depth = 3) Actual Real (1) Fake (0) Real (1) 100% 5% Fake (0) 0% 95% Predicted 19 May 2021 QGAN to Reproduce Calorimeters Outputs 6

Rescale sigmoid function 19 May 2021 QGAN to Reproduce Calorimeters Outputs 7

Rescale sigmoid function 19 May 2021 QGAN to Reproduce Calorimeters Outputs 7

CV GAN test ü Latent vector of size 1, following normal distribution ü Using

CV GAN test ü Latent vector of size 1, following normal distribution ü Using Adam Optimizer depthd = 3, depthg = 4 19 May 2021 depthd = 3, depthg = 6 QGAN to Reproduce Calorimeters Outputs 8

CV GAN test depthd = 3, depthg = 6 19 May 2021 QGAN to

CV GAN test depthd = 3, depthg = 6 19 May 2021 QGAN to Reproduce Calorimeters Outputs 9

Increase batchsize depthd = 3, depthg = 6 19 May 2021 QGAN to Reproduce

Increase batchsize depthd = 3, depthg = 6 19 May 2021 QGAN to Reproduce Calorimeters Outputs 10

Current step ü Testing GAN with different parameters ü Test different loss function (Wasserstein

Current step ü Testing GAN with different parameters ü Test different loss function (Wasserstein Loss) ü Difficulty : Requires a long time for simulation Ex : 50 min for one epoch with 1, 000 samples, depthd = 3, depthg = 6 ü Come back to classical network to test it is possible to reproduce the targeted “image” set 19 May 2021 QGAN to Reproduce Calorimeters Outputs 11

Questions? THANK YOU 19 May 2021 QGAN to Reproduce Calorimeters Outputs 12

Questions? THANK YOU 19 May 2021 QGAN to Reproduce Calorimeters Outputs 12

Generative adversarial networks GANs Kh wong Generative adversarialGenerative adversarial networks GANs Kh wong Generative adversarial
Dual PQC Quantum Generative Adversarial Networks to ReproduceDual PQC Quantum Generative Adversarial Networks to Reproduce
GENERATIVE ADVERSARIAL NETWORKS IN TMVA ANUSHREE RANKAWAT GENERATIVEGENERATIVE ADVERSARIAL NETWORKS IN TMVA ANUSHREE RANKAWAT GENERATIVE
Project 5 Generative Adversarial Network Zhifei Zhang GenerativeProject 5 Generative Adversarial Network Zhifei Zhang Generative
Image recognition Defense adversarial attacks using Generative AdversarialImage recognition Defense adversarial attacks using Generative Adversarial
Adversaries Adversarial examples Adversarial examples Ostrich Adversarial examplesAdversaries Adversarial examples Adversarial examples Ostrich Adversarial examples
Calorimeters Georg Viehhauser Calorimeters HT 07 The principlesCalorimeters Georg Viehhauser Calorimeters HT 07 The principles
Outline of CEPC Calorimeters CDR CEPCCalo Group CalorimetersOutline of CEPC Calorimeters CDR CEPCCalo Group Calorimeters
Using Generative Adversarial Networks for Fast Simulation inUsing Generative Adversarial Networks for Fast Simulation in
Generative Adversarial Networks MLCV 182 Lecturer Oren FreifeldGenerative Adversarial Networks MLCV 182 Lecturer Oren Freifeld
A StyleBased Generator Architecture for Generative Adversarial NetworksA StyleBased Generator Architecture for Generative Adversarial Networks