intltechventures.blogspot.com: Quantum Computing

Showing posts with label Quantum Computing. Show all posts

2025-05-15

2025-05-15 Thursday - Book Review - Building Quantum Software in Python: A developer's guide

[image source: Amazon.com]

Building Quantum Software in Python: A developer's guide
by Constantin Gonciulea, and Charlee Stefanski

Review:

An excellent book that will walk you through the principles, concepts, theory, and practical techniques of building quantum computing software, with Python.

The quality of the writing is "crisp" - a word of praise I reserve for the best authors.

Full Disclosure:

I was invited to participate in early manuscript reviews, by Constantin.

2023-12-07

2023-12-07 Thursday - Quantum Computing Conference Talks

IBM Quantum Summit 2023

(11 videos, playlist)
https://www.youtube.com/playlist?list=PL0VD16H1q5IOwPw0WPml60LQdZg4dFdrd

2023 Mathematical Aspects of Quantum Learning Workshop (UCLA, IPAM)

Institute for Pure & Applied Mathematics (IPAM)

(22 videos, playlist)
https://www.youtube.com/playlist?list=PLHyI3Fbmv0SckwZK0xfc7itiq9nLWJeUF

https://www.ipam.ucla.edu/programs/workshops/workshop-ii-mathematical-aspects-of-quantum-learning/?tab=overview

https://www.ipam.ucla.edu/programs/workshops/workshop-ii-mathematical-aspects-of-quantum-learning/?tab=schedule

"Recent results have hinted at the role quantum computing and technology may play in the future of machine learning, but much remains to be understood. For example, it has been shown that quantum computers can offer exponential improvements in learning from quantum data that comes from the physical world, and that compact quantum models can allow us to sample from probability distributions that seem inaccessible to traditional computing devices. In addition, general purpose quantum algorithms exist to dramatically speed up a number of subroutines that are pivotal in existing machine learning systems, but come with challenging caveats or have led to novel classical algorithm counterparts that challenge the advantage provided by quantum systems. However, fully grasping these results and connecting them to problems of interest today remains challenging for many reasons."

"In this workshop, we hope to bring together experts from mathematics, quantum algorithms, and machine learning to better understand this intersection and reach the full potential of quantum computing and machine learning. This includes, but is not limited to, the ways in which quantum computers can accelerate existing machine learning algorithms, how we process inherently quantum data with either classical or quantum computers, and ways in which machine learning can change how we operate quantum devices. We hope to identify a number of open questions of interest in each area, and draw strong connections to the mathematical foundations of both quantum computing and machine learning."

2020-06-21

2020-06-21 Sunday - Manning Publications - 2020 Books of Interest

There are many excellent new titles (and some updated 2nd editions) - coming later this year, that may be of interest (and benefit) to you (or, members of your organization) - from Manning Publications Co. , and I look forward to hopefully having a chance to review many of them.

Check them out here (in publication date order):
https://www.manning.com/catalog/sort/sort-by-date

For example:

GraphQL in Action
Kubernetes in Action, Second Edition
Blockchain in Action
Machine Learning with TensorFlow, Second Edition
Microservices Security in Action
API Security in Action
Graph Databases in Action
Grokking Deep Reinforcement Learning
Rust in Action
Serverless Architectures on AWS, Second Edition
Bootstrapping Microservices with Docker, Kubernetes, and Terraform
Kafka in Action
Math for Programmers
Modern Fortran
Terraform in Action
React Hooks in Action
Deep Learning with Python, Second Edition
Grokking Machine Learning
Microservices in .NET Core, Second Edition
Quantum Computing for Developers
Core Kubernetes
Exploring Data with R
Functional Programming in Kotlin
Getting Started with Natural Language Processing
GitOps and Kubernetes
Istio in Action
R in Action, Third Edition
PySpark in Action
Spring Security in Action
Getting Started with Kubernetes
Spring in Action, Sixth Edition

2019-11-17

2019-11-17 Sunday - Quantum Factorization Papers

This is a placeholder blog post - as part of a deep-dive into Quantum Computing that I'm doing.

Background reading:

https://en.wikipedia.org/wiki/Shor%27s_algorithm
Some additional notes and links to resources I periodically update in a github repository:

https://github.com/intltechventures/Lab.QuantumComputing

Some papers in my reading queue:

Quantum-Kit: Simulating Shor's Factorization of 24-Bit Number on Desktop

https://arxiv.org/abs/1908.07187

How to factor 2048 bit RSA integers in 8 hours using 20 million noisy qubits

https://arxiv.org/abs/1905.09749

Factoring semi-primes with (quantum) SAT-solvers

https://arxiv.org/abs/1902.01448

Exact search algorithm to factorize large biprimes and a triprime on IBM quantum computer

https://arxiv.org/abs/1805.10478

Summatory function of the number of prime factors

https://arxiv.org/abs/1801.06906

On speeding up factoring with quantum SAT solvers

https://arxiv.org/abs/1910.09592

2019-11-08

2019-11-08 Friday - Technical Reviewer for Learn Quantum Computing with Python and Q#

With gratitude to the editorial team, I've been added as one of the Technical Reviewers for a new early-access Manning Publications book,

Learn Quantum Computing with Python and Q#
https://www.manning.com/books/learn-quantum-computing-with-python-and-q-sharp

2019-07-18

2019-07-18 Thursday - Quantum Physicist Prof Michelle Simmons - Breakthrough

Quantum leap from Australian research promises super-fast computing power

https://www.theguardian.com/technology/2019/jul/19/quantum-leap-australian-researchers-could-lead-to-much-greater-computing-power

"they have been able to achieve the first two-qubit gate between atom qubits in silicon, allowing them to communicate with each other at a 200 times faster rate than previously achieved at 0.8 nanoseconds."

"In choosing silicon, Simmons said the research team had demonstrated that their atomic-scale circuitry has the lowest electrical noise of any system yet devised to connect to a semiconductor qubit."