Nathan’s Quantum Tech Newsletter: №10 — Open-Source Quantum Tech
This is what I’ve seen in quantum tech this month:
00 ⚙ Focus: Open-Source Quantum Tech
01 🗞 Tech News
10 📰 Research Highlights
11 🎲 Bonus Links
00 ⚙ Focus: Open-Source Quantum Tech
There is a general trend in academia: the growth of open-source software for open science. Quantum tech is part of this transformation.
Open-source code is hosted on freely reachable online repositories, such as Github, and distributed for everyone to tweak it and build upon it. Often this happens in a collaborative way, and it can be seen as just one aspect of the shift to larger teams in academic research. Link
Open science is a growing movement across various research communities, which aims at removing any boundary limiting the dissemination of knowledge. Some of its tools are characteristic of computational research, such as accessible data sets and interactive Python notebooks, ensuring that scientific results can be easily reproduced. Link
But what is the difference, one might say, from the usual implementation of numerical studies? After all, physicists have been among the first researchers to adopt computational tools, back in the days when punched cards meant counterculture innovation. The main difference indeed lies in the way code is developed and distributed.
Unlike the long programs of the past, sometimes heavy on syntax or hard to debug, interactive notebooks equip scientists with the modern notepads. Not only they are used to jot down ideas, test them, and visualize results immediately, but they are affecting the very way scientific knowledge itself develops and spreads. Link
Moreover, the features determining the success of a given programming language have shifted. Take Python: it is known to be inherently slower than other languages, but its simple syntax and flexibility has made it the fastest-growing major programming language in recent years. Link
If Python has rapidly become the language of choice for most of open-source collaborative projects, it is also because it now offers a vibrant ecosystem of open-source libraries. From plotting to machine learning to quantum algorithm design, the strength of these libraries lies in their modular and stackable configuration, which can adapt to the requirements of the user. Link
And then there are features characteristic of the quantum tech ecosystem.
It is now possible for anyone to launch a program to run it on a quantum machine from the cloud. While the usefulness of this option might now be limited — beyond some research-related aspects — the very idea of this possibility is driving thousands of non-experts to tinker with quantum circuits online, for example on the IBM Q. Link
The learning curve is still steeper for quantum mechanics than for other areas, such as the implementation of machine learning, but at the same time there is a growing community of young coders eager to learn quantum information through coding. Link
The quantum tech ecosystem is being affected by these trends, both in academia and industry.
On the one hand, quantum computing software faces a series of unique challenges. Since it is designed to be run on a quantum compiler, it needs to be converted from high-level user instructions into low-level machine code, eventually implemented on a quantum computer. As quantum computing technology is still in its infancy, also these passages are under experimental development, and the open-source approach might play a role there too.
On the other hand, quantum computation experiments are not the whole story. Indeed there is an increasingly large pool of tools designed, developed and maintained to study quantum physics or just particular aspects of quantum theory. For example, thousands of researchers, every day, simulate quantum mechanics phenomena from their laptops, using open-source software libraries as QuTiP, the quantum toolbox in Python. Link
All of these factors are contributing to create a high demand of a new professional figure: the quantum-software engineer. Startups are looking for new hires familiar with quantum mechanics. Research groups are eager to find someone able to optimize their code and consistently build upon existing projects through continuous integration.
And while only experts might master specific sets of skills, a larger number of researchers is benefiting from learning how to use the standard tools of open-source coding.
01 🗞 Tech News
Technion, Israel’s Institute of Technology, received a $50 m gift from a private donor to foster research in quantum technology with a new centre. Gadi Eisenstein and Mordechai Segev will be among the leaders of the center. Link
IBM established a formal partnership with several existing quantum tech startups. Link
Strangeworks is a quantum computing startup that has raised $4 million in funding, founded William Hurley, a serial entrepreneur with no experience in quantum tech. Link
Zapata Computing, focusing on software for quantum computing, has raised $5.4 million in funding. The startup is founded by Alán Aspuru-Guzik, professor of chemistry at Harvard moving to the University of Toronto. Link
Qubit Protocol is an Australian project that aims to be a platform for crowdfunding quantum startups through cryptocurrency tokens. Quantum information researchers Marco Tomamichel, Gavin Brennen, and Troy Lee are part of the team. Link
Quantum machine learning ideas for the 2018–2019 batch of the Creative Destruction Lab program in Toronto. Deadline for applications is May 10th. Link
Quantum computers strive to get out of the lab. Link
An editorial on Nature Physics on the possibilities of the quantum tech industry. Link
Are we at the verge of a new era in quantum computing, or is it just the beginning of the quantum equivalent of the “AI winter”? Link
10 📰 Research Highlights
Towards braiding Majorana quasi-particles. Link
Observation of entangled states of a fully controlled 20-qubit system. Link
Videos from the Bilbao workshop on quantum simulations. Link
Charge quantum interference device. Link
A proposal to test entanglement on a telecommunication channel between Earth and Moon. Link (For my previous focus on recent space quantum communication results see here. Link)
A strongly interacting polaritonic quantum dot. Link
Building one molecule from a reservoir of two atoms. Link
Squeezing Enhances Quantum Synchronization. Link
Quantum metrology with quantum-chaotic sensors. Link
Quantum chemistry calculations on a trapped-ion quantum simulator. Link
A review on quantum metrology with nonclassical states of atomic ensembles. Link1 Link2
Architectures for quantum simulation showing a quantum speedup. Link
Bridging many-body quantum physics and deep learning via tensor networks. Link
Quantum chemistry calculations on a trapped-ion quantum simulator. Link
Quantum algorithm implementations for beginners. Link
Quantum mechanics could solve cryptography’s random number problem. Link
White paper from the EU Quantum Technologies Flagship Program. Link
Using quantum machine learning to analyze data in infinite-dimensional spaces. Link
Quantum chemistry at Google. Link
11 🎲 Bonus Links
Bedtime stories: Quantum computing for babies. Link
Bohr vs Einstein. Link
The certainty of randomness. Link
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© Nathan Shammah — 2018 and beyond.
