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It is a common misconception that quantum computers are not yet ready for applications and the technology still has many years before becoming useful. In this article we will take a look at some of the basic principles of programming a quantum computer and address this misconception. We will look at free, open-source software such as QISKit from IBM, as well as the Quantum Machine Learning software PennyLane. We will also explain how you can run your programs on actual quantum computers in the cloud at IBM. In a follow-up article we will talk about some applications in machine learning that are ready for use currently to anyone with a bit of curiosity.

Circa 2011 essentially a magnet could be a battery and cpu and a gpu with magnonics.

Harvard physicists have expanded the possibilities for quantum engineering of novel materials such as high-temperature superconductors by coaxing ultracold atoms trapped in an optical lattice — a light crystal — to self-organize into a magnet, using only the minute disturbances resulting from quantum mechanics. The research, published in the journal Nature, is the first demonstration of such a “quantum magnet” in an optical lattice.

As modern technology depends more and more on materials with exotic quantum mechanical properties, researchers are coming up against a natural barrier.

Continue reading “The ‘quantum magnet’” »

Error free qubits o.,o.

Physicists at MIT and elsewhere have observed evidence of Majorana fermions—particles that are theorized to also be their own antiparticle—on the surface of a common metal: gold. This is the first sighting of Majorana fermions on a platform that can potentially be scaled up. The results, published in the Proceedings of the National Academy of Sciences, are a major step toward isolating the particles as stable, error-proof qubits for quantum computing.

In particle physics, fermions are a class of elementary particles that includes electrons, protons, neutrons, and quarks, all of which make up the building blocks of matter. For the most part, these particles are considered Dirac fermions, after the English physicist Paul Dirac, who first predicted that all fermionic fundamental particles should have a counterpart, somewhere in the universe, in the form of an antiparticle—essentially, an identical twin of opposite charge.

Continue reading “First sighting of mysterious Majorana fermion on a common metal” »

In nuclear physics, like much of science, detailed theories alone aren’t always enough to unlock solid predictions. There are often too many pieces, interacting in complex ways, for researchers to follow the logic of a theory through to its end. It’s one reason there are still so many mysteries in nature, including how the universe’s basic building blocks coalesce and form stars and galaxies. The same is true in high-energy experiments, in which particles like protons smash together at incredible speeds to create extreme conditions similar to those just after the Big Bang.

Fortunately, scientists can often wield simulations to cut through the intricacies. A simulation represents the important aspects of one system—such as a plane, a town’s traffic flow or an atom—as part of another, more accessible system (like a computer program or a scale model). Researchers have used their creativity to make simulations cheaper, quicker or easier to work with than the formidable subjects they investigate—like proton collisions or black holes.

Simulations go beyond a matter of convenience; they are essential for tackling cases that are both too difficult to directly observe in experiments and too complex for scientists to tease out every logical conclusion from basic principles. Diverse research breakthroughs—from modeling the complex interactions of the molecules behind life to predicting the experimental signatures that ultimately allowed the identification of the Higgs boson—have resulted from the ingenious use of simulations.

Unlike the magnetic materials used to make a typical memory device, antiferromagnets won’t stick to your fridge. That’s because the magnetic spins in antiferromagnets are oppositely aligned and cancel each other out.

Scientists have long theorized that antiferromagnets have potential as materials for ultrafast stable memories. But no one could figure out how to manipulate their magnetization to read and write information in a memory device.

Now, a team of researchers at Berkeley Lab and UC Berkeley working in the Center for Novel Pathways to Quantum Coherence in Materials, an Energy Frontier Research Center funded by the U.S. Department of Energy, have developed an antiferromagnetic switch for computer memory and processing applications. Their findings, published in the journal Nature Materials, have implications for further miniaturizing computing devices and personal electronics without loss of performance.

Seeqc, a startup that is part of a relatively new class of quantum computing companies that is looking at how to best use classical computing to manage quantum processors, today announced that it has raised $5 million from M Ventures, the strategic corporate venture capital arm of Merck, the German pharmaceutical giant. Merck will be a strategic partner for Seeqc and will help it to develop its R&D efforts to develop useful application-specific quantum computers.

With this, New York state-based Seeqc has now raised a total of $11 million, including a recent $6.8 million seed round that included BlueYard Capital, Cambium, NewLab and the Partnership Fund for New York City.

Since developing new pharmaceuticals is an obvious use case for quantum computing, it makes sense that large pharmaceutical companies are trying to get ahead of their competitors by making strategic investments in companies like Seeqc.

Since the original work on Bose–Einstein condensation^1,2, the use of quantum degenerate gases of atoms has enabled the quantum emulation of important systems in condensed matter and nuclear physics, as well as the study of many-body states that have no analogue in other fields of physics³. Ultracold molecules in the micro- and nanokelvin regimes are expected to bring powerful capabilities to quantum emulation⁴ and quantum computing⁵, owing to their rich internal degrees of freedom compared to atoms, and to facilitate precision measurement and the study of quantum chemistry⁶. Quantum gases of ultracold atoms can be created using collision-based cooling schemes such as evaporative cooling, but thermalization and collisional cooling have not yet been realized for ultracold molecules. Other techniques, such as the use of supersonic jets and cryogenic buffer gases, have reached temperatures limited to above 10 millikelvin^7,8. Here we show cooling of NaLi molecules to micro- and nanokelvin temperatures through collisions with ultracold Na atoms, with both molecules and atoms prepared in their stretched hyperfine spin states. We find a lower bound on the ratio of elastic to inelastic molecule–atom collisions that is greater than 50—large enough to support sustained collisional cooling. By employing two stages of evaporation, we increase the phase-space density of the molecules by a factor of 20, achieving temperatures as low as 220 nanokelvin. The favourable collisional properties of the Na–NaLi system could enable the creation of deeply quantum degenerate dipolar molecules and raises the possibility of using stretched spin states in the cooling of other molecules.

Rydberg atoms, which are atoms in a highly excited state, have several unique and advantageous properties, including a particularly long lifetime and large sensitivities to external fields. These properties make them valuable for a variety of applications, for instance for the development of quantum technologies.

In order for Rydberg atoms to be effectively used in quantum technology, however, researchers first need to be able to trap them. While a number of studies have demonstrated the trapping of Rydberg atoms using magnetic, electric, or laser technology, the trapping times achieved so far have been relatively short, typically around 100μs.

Researchers at Laboratoire Kastler Brossel (LKB) have recently achieved a longer 2-D laser trapping time of circular Rydberg atoms of up to 10 ms. The method they employed, outlined in a paper published in Physical Review Letters, could open up exciting new possibilities for the development of quantum technology.

Adilson Motter, Northwestern University

After 12 successful seasons, “The Big Bang Theory” has finally come to a fulfilling end, concluding its reign as the longest running multicamera sitcom on TV.

If you’re one of the few who haven’t seen the show, this CBS series centers around a group of young scientists defined by essentially every possible stereotype about nerds and geeks. The main character, Sheldon (Jim Parsons), is a theoretical physicist. He is exceptionally intelligent, but also socially unconventional, egocentric, envious and ultra-competitive. His best friend, Leonard (Johnny Galecki), is an experimental physicist who, although more balanced, also shows more fluency with quantum physics than with ordinary social situations.