Nathan’s Quantum Tech Newsletter: №15
This is what I’ve seen in quantum tech in the last month, November 2018:
00 🗞 Tech News
01 📰 Research Highlights
10 🎲 Bonus Links
00 🗞 Tech News
Two recent reports on quantum computing provide valuable information to non-experts. These are probably the most thorough documents tailored for an audience outside that of academic circles, after Jason Palmer’s extensive reporting on quantum technologies for The Economist in early 2017.
The first document is an extensive report by BCG Munich on quantum computing. This is the most detailed such document on this space from a strategy consultancy or corporate player, notably devoid of unnecessary hype. Lots of information to navigate this field, including information on players, startup rounds and maturity of applications. Also featuring: Quantika, among players in the first figure, and the BCG matrix, or better its quantum-advantage version. Link
A recent workshop provided the opportunity for a very thorough, technical, but at the same time accessible, report on the stage of quantum computing from the perspective of experts of the field, aimed at computer scientists and non-experts, committed by the Computer Research Association. Nice plots. Link
Both reports capture the growing effort of Honeywell, a defense contractor, in building an experimental quantum computing team, joining competitors.
In an interview accompanying BCG’s first white paper, Chad Rigetti discloses that its company has so far raised almost $120 mln in funding. The company plans to launch a 128-qubit quantum processor by next Summer. Link
Daimler, the car maker, is looking into quantum computing with Google research. Link
Google researchers have started a series of videos on quantum computers and how to program them. Link
01 📰 Research Highlights
Pennylane is an open-source library for quantum machine learning released by Xanadu, with extensive documentation. Link
Quantum communication with time-bin encoded microwave photons. Link
A review on recent advances in photonic quantum sensing. Link
Experimental simultaneous learning of multiple non-classical correlations. Link
Spin squeezing of 10¹¹ atoms. Link
Neuromorphic computing in Ginzburg-Landau lattice systems. Link
Intel’s researchers performed a study on the impact of qubit connectivity on quantum algorithm performance, showing that limited qubit connectivities can still compete with all-to-all architectures in some special cases. Link
Quantum compilation and circuit optimisation via energy dissipation. Link
Quantum data classification by dissipation. Link
Hamiltonian engineering with constrained optimization for quantum sensing and control. Link
Mesoscopic two-mode entangled and steerable states of 40,000 atoms in a Bose-Einstein condensate interferometer. Link
Quantum computation of molecular vibrations. Link
Direct observation of topology from single-photon dynamics on a photonic chip. Link
Deterministic and generalized framework for unsupervised learning with restricted Boltzmann machines. Link
Networks of non-equilibrium condensates for global optimization. Link
Quantum computational finance: quantum algorithm for portfolio optimization. Link
An artificial neuron implemented on an actual quantum processor. Link
10 🎲 Bonus Links
‘Science is getting less bang for its buck’, The Atlantic runs an article, co-authored by Michael Nielsen, in which is argued that we have entered a phase of stagnation in scientific productivity. Link
‘The Kilogram is dead. Long live the kilogram!’. The New York Times reports on how the new standard of mass is now measured through Planck’s constant. Link
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