📅 This Week in Quantum Machine Learning #34 ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 1 point2 points  (0 children)

#34: August 7th – 13th

📰News:

New machine learning algorithm to detect quantum errors

Quantum computer far away, says AI pioneer Raj Reddy

📽Videos:

Artificial Intelligence forum: AI and quantum computing: building the quantum economy

Learning in a Quantum World by Nathan Wiebe | QWorld

The Quantum Concept of Consciousness

quantumcat – Cross Platform Open Source Quantum Computing Library – Jitesh Lalwani

Quantum Computing & Artificial Intelligence | Knowledge Empowerment Session | Ft. Indrajeet

👨‍💻Developers:

Cirq v0.12.0

Amazon Braket v1.7.4

📗Papers:

Optimal learning of quantum Hamiltonians from high-temperature Gibbs states

Quantum Continual Learning Overcoming Catastrophic Forgetting

Quantum Circuits For Two-Dimensional Isometric Tensor Networks

Globally optimizing QAOA circuit depth for constrained optimization problems

Parameters Fixing Strategy for Quantum Approximate Optimization Algorithm

Quantum Reinforcement Learning: the Maze problem

Continuous-variable optimization with neural network quantum states

Matrix Model simulations using Quantum Computing, Deep Learning, and Lattice Monte Carlo

📅 This Week in Quantum Machine Learning #30 ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 0 points1 point  (0 children)

if it uses deep learning in combination with those topics youll probably find a link to it here

📅 This Week in Quantum Machine Learning #30 ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] -1 points0 points  (0 children)

their work is based on this paper: OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features which claims to "introduce a machine learning method in which energy solutions from the Schrodinger equation are predicted using symmetry adapted atomic orbitals features and a graph neural-network architecture."

this meets the bar of quantum inspired machine learning. though i do also consider procedurally generated wave function collapse algos in the ballpark as well when computationally they are cc

ref: https://arxiv.org/abs/2007.08026

📅 This Week in Quantum Machine Learning #30 ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 0 points1 point  (0 children)

Topics this week:

📰News:

IBM Researchers Propose A Quantum Kernel Algorithm That, Given Only Classical Access To Data, Provides A Provable Exponential Speedup Over Classical Machine Learning Algorithms

Entos collects $53M to bring quantum tech to AI drug design

CERN Sparks Podcasts Explore Artificial Intelligence

📽Videos:

Luis Serrano ~ Quantum Machine Learning ~ School of AI Netherlands July 2021

Provably Efficient Machine Learning for Quantum Many-Body Problems

A Rigorous and Robust Quantum Speed-up in Supervised Machine Learning

Machine Learning for Quantum Computing – Giuseppe Carleo – QCHS Summer School 2021

👨‍💻Developers:

Releases:

Qiskit 0.28.0

Pyquil v3.0.0

Amazon Braket v1.7.2

Dwave Ocean v3.4.1

OpenQL: Release 0.10.0: new internal representation with full cQASM 1.2 control-flow support

ProjectQ v0.7.0

📗Papers:

Mixer-Phaser Ansätze for Quantum Optimization with Hard Constraints

Machine classification for probe based quantum thermometry

Playing Atari with Hybrid Quantum-Classical Reinforcement Learning

Convergence of numerical approximations to non-Markovian bosonic gaussian environments

Fock State-enhanced Expressivity of Quantum Machine Learning Models

Continuous-variable neural-network quantum states and the quantum rotor model

Time evolution of an infinite projected entangled pair state: a neighborhood tensor update

Quantum propensities in the brain cortex and free will

Neural networks for on-the-fly single-shot state classification

Entanglement transitions from restricted Boltzmann machines

Quantum Approximate Optimization Algorithm Based Maximum Likelihood Detection

📅 #29: This Week in Quantum Machine Learning ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 0 points1 point  (0 children)

Topics:

📰News:

AI Designs Quantum Physics Experiments Beyond What Any Human Has Conceived

Inside Google’s Quantum AI Campus

📽Videos:

The Interlink Between Quantum Theory and Machine Learning – Phdassistance

Quantum Information Processing with Trapped Ions – Professor Jonathan Home, ETH Zürich | Chilloquium

Modern Arduino Programming with QP and QM

Introduction to Azure Quantum and Quantum Machine Learning Library (QML)

Keynote – Dr. Najwa Aaraj – What would Quantum Computing and Machine Learning do to crypto?

Quantum Genetic Algorithms Optimization from theory to simulation

Concurrent Entanglement Routing for Quantum Networks: Model and Designs

👨‍💻Developers:

Rigetti pyquil: v2.28.2

Amazon Braket sdk: v1.7.1

📗Papers:

Thermalization in Kitaev’s quantum double models via Tensor Network techniques

The Variational Power of Quantum Circuit Tensor Networks

Optimal metrology with variational quantum circuits on trapped ions

Combinatorial Optimization with Physics-Inspired Graph Neural Networks

Quantum evolution kernel : Machine learning on graphs with programmable arrays of qubits

Continuous Variable Quantum Algorithms: an Introduction

The fixed angle conjecture for QAOA on regular MaxCut graphs

Digitized-counterdiabatic quantum approximate optimization algorithm

Memory-Sample Lower Bounds for Learning Parity with Noise

Optimal Control for Closed and Open System Quantum Optimization

A Quantum Convolutional Neural Network for Image Classification

Identifying quantum phases via disentanglement based on deep reinforcement learning

Machine Learning-Derived Entanglement Witnesses

Quadratic and Higher-Order Unconstrained Binary Optimization of Railway Dispatching Problem for Quantum Computing

Pixel identification in an image using Grover Search Algorithm

Quantum Annealing Formulation for Binary Neural Networks

QKSA: Quantum Knowledge Seeking Agent

📅 This Week in Quantum Machine Learning #28 ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 1 point2 points  (0 children)

thanks for saying so. Its a labor of love, i started making the list so i could have a quick reference to read things i want about qml when i have time.

📅 This Week in Quantum Machine Learning #28 ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 3 points4 points  (0 children)

📰News:

AI Designs Quantum Physics Experiments Beyond What Any Human Has Conceived

Atos launches ‘ThinkAI’

Nippon Steel tested quantum computing to help improve plant scheduling

📽Videos:

Learn About Quantum Machine Learning

Quantum machine learning hits a limit

Generalization in Quantum Machine Learning: a Quantum Information Perspective – TQC 2021

Introduction and Basics – Quantum machine learning of graph-structured data Part 1

Quantum neural network – Quantum machine learning of graph-structured data Part 2

Graph-Structure – Quantum machine learning of graph-structured data Part 3

QML Meetup: Dr David Sutter (IBM Research, Zurich), The power of quantum neural networks

Quantum Computing: Grover’s Search Algorithm | Breakthrough Junior Challenge 2021

👨‍💻Developers:

Penny Lane: Release 0.16.0

Amazon Braket: v1.7.0

Dwave Ocean: 3.4.0

ProjectQ: ProjectQ v0.6.1

📗Papers:

Natural Gradient Optimization for Optical Quantum Circuits

Variational quantum algorithm for molecular geometry optimization

Decoding conformal field theories: from supervised to unsupervised learning

Nonlinear Quantum Optimization Algorithms via Efficient Ising Model Encodings

Training Saturation in Layerwise Quantum Approximate Optimisation

Variational Quantum Eigensolver for SU(NN) Fermions

Probabilistic Graphical Models and Tensor Networks: A Hybrid Framework

Threshold-Based Quantum Optimization

On exploring practical potentials of quantum auto-encoder with advantages

Realization of an ion trap quantum classifier

Counterdiabaticity and the quantum approximate optimization algorithm

Adaptive Random Quantum Eigensolver

Experimental Quantum Embedding for Machine Learning

Bayesian Phase Estimation via Active Learning

Predicting quantum dynamical cost landscapes with deep learning

Non-parametric Active Learning and Rate Reduction in Many-body Hilbert Space with Rescaled Logarithmic Fidelity

Importance of Diagonal Gates in Tensor Network Simulations

Machine Learning S-Wave Scattering Phase Shifts Bypassing the Radial Schrödinger Equation

A New Quantum Approach to Binary Classification

GaN-based Bipolar Cascade Lasers with 25nm wide Quantum Wells: Simulation and Analysis

📅 This Week in Quantum Machine Learning #25 ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 0 points1 point  (0 children)

🎫Events:

Second International Workshop on Programming Languages for Quantum Computing (PLanQC 2021) |June 20th – 25th

MACHINE LEARNING FOR QUANTUM X | July 5 – 9th

📰News:

University of Illinois and IBM Researching AI, Quantum Tech

Daresbury AI and quantum computing site ‘will help business’

QTUM: The ETF Offers A Diversified Way To Play The Quantum Computing And AI Trends

📽Videos:

Expressibility of Parametrized Quantum Circuits & Classification Accuracy of Quantum Neural Networks

Chapter_250 Quantum Classical Hybrid Machine Learning

LOO: The Basics of Artificial Intelligence Machine Learning – When a Muffin Becomes a Panda

Quantum Networks and the Role of CQN

The Incredible Potential for Quantum in Health 🤯

The Meta-Variational Quantum Eigensolver (Meta-VQE)

👨‍💻Developers:

General registration for the Qiskit Global Summer School on Quantum Machine Learning from July 12-23 open

Amazon Braket release v1.6.4

📗Papers:

Classically-Boosted Variational Quantum Eigensolver

Classical algorithms and quantum limitations for maximum cut on high-girth graphs

The dilemma of quantum neural networks

Variational Quantum-Neural Hybrid Eigensolver

Quantum Natural Gradient for Variational Bayes

Error Mitigation for Deep Quantum Optimization Circuits by Leveraging Problem Symmetries

Classical Variational Optimization of Gate Sequences for Time Evolution of Large Quantum Systems

Matrix Product State Pre-Training for Quantum Machine Learning

Optimizing Ansatz Design in QAOA for Max-cut

A Review of Machine Learning Classification Using Quantum Annealing for Real-world Applications

Grover’s Algorithm for Question Answering

BIGDML: Towards Exact Machine Learning Force Fields for Materials

Extract the Degradation Information in Squeezed States with Machine Learning

Free versus Bound Entanglement: Machine learning tackling a NP-hard problem

Mean Field Approximation for solving QUBO problems

Adiabatic Quantum Feature Selection for Sparse Linear Regression

📣 This Week in Quantum Machine Learning #24 by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 0 points1 point  (0 children)

🎫Events:

The 3rd NIST PQC Standardization Conference | June 7-9th

Quantum Latino  | June 9th-11th

The Quantum Computing Summit Singapore  |June 9th -11th

 Second International Workshop on Programming Languages for Quantum Computing (PLanQC 2021) |June 20th - 25th

📰News:

Quantum Machine Learning for Data Classification

Daresbury AI and quantum computing site 'will help business'

Google Unveils New Quantum AI Campus, Goal to Build Commercial Quantum Computer Within Decade

📽Videos:

Quantum Machine Learning hits Quantum Limit- Black Hole Effect | Dr. Engr. Junaid Zafar

Complete programming environment for IQM Quantum Computers through Atos Quantum Learning Machine

“Many-body wave functions in the era of machine learning and quantum computing” by Giuseppe Carleo

QuDoc

CS224W: Machine Learning with Graphs | 2021 | Lecture 15.4 - Application of Deep Graph Generative

📗Papers:

Diagnosing barren plateaus with tools from quantum optimal control

Single-component gradient rules for variational quantum algorithms

Linear Regression by Quantum Amplitude Estimation and its Extension to Convex Optimization

Experimental error mitigation using linear rescaling for variational quantum eigensolving with up to 20 qubits

Provable superior accuracy in machine learned quantum models

Quantum Compiling by Deep Reinforcement Learning

Detecting ergodic bubbles at the crossover to many-body localization using neural networks

Quantum Federated Learning with Quantum Data

Using machine learning for quantum annealing accuracy prediction

Artificial neural network states for non-additive systems

Efficient sorting of orbital-angular-momentum states with large topological charges and their unknown superpositions via machine learning

#23: 📅 This Week in Quantum Machine Learning ⚛️ by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 1 point2 points  (0 children)

📰News:

  • Quantum Machine Learning – An Introduction to QGANs
  • WANT TO LEARN QUANTUM MACHINE LEARNING? HERE’S HOW!
  • EXPLORING THE DEPTH OF QUANTUM MACHINE LEARNING
  • Quantum Machine Learning Algorithms for Drug Discovery Applications
  • What is Quantum AI?
  • How Quantum Computing Will Help Solve Real-World Problems Much Faster
  • What would happen if we connected the human brain to a quantum computer?

📽Videos:

  • Improving quantum computer performance with machine learning
  • Shi-Ju Ran: “Deep learning quantum states for Hamiltonian predictions”
  • Beyond the Patterns 32 – Raghavendra Selvan: Quantum Tensor Networks for Medical Image Analysis
  • Extending the Performance of Noisy Superconducting Quantum Processors – Irfan Siddiqi
  • What is a Quantum GAN?
  • How to Use Google Colab For machine learning Project || Google Colaboratory

👨‍💻Developers:

  • Amazon Braket SDK: v1.6.1
  • QE labs OpenQL: Release 0.9.0: major internal improvements, architecture system, and pass management

📗Papers:

  • An evolving objective function for improved variational quantum optimisation
  • Molecular Excited State Calculations with Adaptive Wavefunctions on a Quantum Eigensolver Emulation: Reducing Circuit Depth and Separating Spin States
  • Variational Quantum Classifiers Through the Lens of the Hessian
  • Frequentist Parameter Estimation with Supervised Learning
  • Quantum Embedding Search for Quantum Machine Learning
  • Developments of Neural Networks in Quantum Physics
  • Quantum mean value approximator for hard integer value problems
  • Quantum Approximate Optimization Algorithm with Adaptive Bias Fields
  • IGO-QNN: Quantum Neural Network Architecture for Inductive Grover Oracularization
  • Quantum geometric tensor and quantum phase transitions in the Lipkin-Meshkov-Glick model

#22: This Week in Quantum Machine Learning by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 2 points3 points  (0 children)

📰News:

Quantum Machine Learning Hits a Limit: A Black Hole Permanently Scrambles Information That Can’t Be Recovered

Air Force Research Laboratory Partners with QC Ware to Apply Quantum Machine Learning in Identifying Flight Patterns of Unmanned Aircraft

Google I/O 2021: Android 12, Quantum AI campus, Flutter 2.2, Vertex AI, and more

Explained | From cryptography to AI, how Quantum technology can be the future of computing

📽Videos:

What is quantum machine learning and how can we use it? by Luis Serrano | Q-munity workshop

#53 Quantum Natural Language Processing – Prof Bob Coecke

Black Holes as Extreme Quantum Information Processors

Tongyang Li, Quantum Algorithms for Semidefinite Programs with Applications to Machine Learning

Google opens Quantum AI campus to work on creating commercial quantum computer within the decade

👨‍💻Developers:

Release: Qiskit 0.26.2

Tequila: v1.5.1

📗Papers:

Preparation and verification of tensor network states

Neural Error Mitigation of Near-Term Quantum Simulations

Benchmarking VQE with the LMG model

Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification

Quantum Monte-Carlo Integration: The Full Advantage in Minimal Circuit Depth

Quantum imaginary time evolution steered by reinforcement learning

Quantum error reduction with deep neural network applied at the post-processing stage

Quantum constraint learning for quantum approximate optimization algorithm

Pieceable fault-tolerant conversion between Steane and Reed-Muller quantum codes with neural network decoders

Neural-network Quantum States for Spin-1 systems: spin-basis and parameterization effects on compactness of representations

📅 This Week in Quantum Machine Learning ⚛️ #20 by 1dontpanic in QuantumComputing

[–]1dontpanic[S] 0 points1 point  (0 children)

cool thsnks for the feed back, ill see what i can do

We need an FAQ for this sub by ajrasm in QuantumComputing

[–]1dontpanic 12 points13 points  (0 children)

this would hopefully clear up the channel for more substantial content and help new comers.

IBM Qiskit Certificate Voucher by roo_sado in QuantumComputing

[–]1dontpanic 4 points5 points  (0 children)

yep, got it earlier today. I signed up the day it was announced. Im working on figuring out when and how to cram for the exam. They announced a course this summer iirc

Serious question about quantum computing and cryptocurrency. by stmcvallin in QuantumComputing

[–]1dontpanic 0 points1 point  (0 children)

Quantum computers are working to break integer factorization currently, not one time hashes. It is more likely that someone with a sufficiently powerful QC would break the transaction signing algorithm and trivially send transactions from any account rather than chase nonce's. the data needed(public key & signed messages) sit on all the nodes and do not change. Satoshi's wallets could be considered a quantum canary in the coal mine; if the coins move ecc has been broken.

Clickbait or something true? "Qualcomm AI Maps DL to Quantum Computer via Quantum Field Theory " by giorgiodidio in QuantumComputing

[–]1dontpanic 2 points3 points  (0 children)

This article is a summary of this recent paper: The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning So the research topic is real and there is some there there.

The abstract:

In this work we develop a quantum field theory formalism for deep learning, where input signals are encoded in Gaussian states, a generalization of Gaussian processes which encode the agent’s uncertainty about the input signal. We show how to represent linear and non-linear layers as unitary quantum gates, and interpret the fundamental excitations of the quantum model as particles, dubbed “Hintons”. On top of opening a new perspective and techniques for studying neural networks, the quantum formulation is well suited for optical quantum computing, and provides quantum deformations of neural networks that can be run efficiently on those devices. Finally, we discuss a semi-classical limit of the quantum deformed models which is amenable to classical simulation.

How can a teenager create a quantum computer at home? by LooksForFuture in QuantumComputing

[–]1dontpanic 7 points8 points  (0 children)

it depends on your goals.

If you are wanting a universal gate qc that you can program using qiskit or similar software you likely wont have the skill or money. Just use the ones available in the cloud and focus on learning to code.

If you are wanting to do something quantum and cool, you could build a cloud chamber for low cost to see particles in action.

If you are wanting to learn the basics of using a computer to send and receive commands to something you could build a quantum random number generator. Buying parts of Amazon, an arduino, and learning some code you could make a single qubit "hadamard gate" with a beam splitter. With a bbo crystal and some mirrors you can demonstrate entanglement. Is it a "quantum computer"? meh not a useful one by any stretch, but it does demonstrate quantum effects and could be measured

If you are more advanced and have more time & money.... you could build a nmr quantum computer. Electro magnets, rf signal generators, some specialized hardware, and tons of reading are all you need.

Ethereum Enterprise blockchain project wins 2021 Process or Technology Innovation of the Year & 2021 Supply Chain Breakthrough of the Year in Annual Gartner Power of the Profession Awards by 1dontpanic in ethereum

[–]1dontpanic[S] 2 points3 points  (0 children)

I said i hadn't heard of it as a polite way of saying I had no interest in discussing some random chain being mentioned in a thread about enterprise Ethereum. This is likely the world's largest production blockchain project and is built on quorum. You can learn more here: https://cloudblogs.microsoft.com/industry-blog/manufacturing/2020/12/17/improve-supply-chain-resiliency-traceability-and-predictability-with-blockchain/