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Quantum computing with single photons getting closer to reality

(Phys.org)—One promising approach for scalable quantum computing is to use an all-optical architecture, in which the qubits are represented by photons and manipulated by mirrors and beam splitters. So far, researchers have demonstrated this method, called Linear Optical Quantum Computing, on a very small scale by performing operations using just a few photons. In an attempt to scale up this method to larger numbers of photons, researchers in a new study have developed a way to fully integrate single-photon sources inside optical circuits, creating integrated quantum circuits that may allow for scalable optical quantum computation.

The researchers, Iman Esmaeil Zadeh, Ali W. Elshaari, and coauthors, have published a paper on the integrated quantum circuits in a recent issue of Nano Letters.

As the researchers explain, one of the biggest challenges facing the realization of an efficient Linear Optical Quantum Computing system is integrating several components that are usually incompatible with each other onto a single platform. These components include a single-photon source such as quantum dots; routing devices such as waveguides; devices for manipulating such as cavities, filters, and quantum gates; and single-photon detectors.

The Quantum Fluid Inside Neutron Stars

In 1937 Pyotr Kapitsa and John F. Allen discovered a strange behavior of ultracold liquids known as superfluidity. A superfluid is a fluid with no viscosity, basically a frictionless liquid. Without viscosity, the fluid has no way to dampen its motion. Because of this, superfluids have some pretty unusual behaviors. If a bit of superfluid is suspended in an open container, it will creep up along the walls, then drip down to a lower container. It can flow through tiny pores that regular liquids can’t, and can create fountains that could flow forever. This seeming defiance of gravity and common sense is due to the fact that its behavior is rooted in quantum physics. Though it is not a truly quantum state such as a Bose-Einstein condensate, it shares some commonality with it. In the lab, superfluids are only seen at temperatures barely above absolute zero. The most common example, helium-4, becomes superfluid when cooled below 2.17 K. So it might seem odd that superfluids are also found in the hot interiors of neutron stars.

A neutron star is a stellar remnant formed with a star runs out of hydrogen and heavier elements to fuse. After a star explodes as a supernova, the remaining core of the star collapses under its own weight to the point that only the pressure of nuclei can counter the force of gravity. A neutron star has a mass of about two Suns, but are only about 20 kilometers in diameter. They have a dense atmosphere of carbon only a few centimeters thick, and a thin crust of iron nuclei. In the interior of a neutron star, nuclei are pushed together ever more tightly, and reach a point where the nuclei can’t hold themselves together. As a result, individual neutrons “drip” out, and sink into the star’s core, forming a neutron fluid. As a neutron star cools, this neutron fluid transitions to a superfluid state. This happens not at a few degrees Kelvin, but at 500 to 800 million Kelvin. The interior of a neutron star is a hot superfluid sea.

Physicists demonstrate a quantum Fredkin gate

Researchers from Griffith University and the University of Queensland have overcome one of the key challenges to quantum computing by simplifying a complex quantum logic operation. They demonstrated this by experimentally realising a challenging circuit—the quantum Fredkin gate—for the first time.

“The allure of quantum computers is the unparalleled processing power that they provide compared to current technology,” said Dr Raj Patel from Griffith’s Centre for Quantum Dynamics.

“Much like our everyday computer, the brains of a quantum computer consist of chains of logic gates, although quantum logic gates harness quantum phenomena.”

Unlocking the gates to quantum computing

Researchers from Griffith University and the University of Queensland have overcome one of the key challenges to quantum computing by simplifying a complex quantum logic operation. They demonstrated this by experimentally realising a challenging circuit — the quantum Fredkin gate — for the first time.

“The allure of quantum computers is the unparalleled processing power that they provide compared to current technology,” said Dr Raj Patel from Griffith’s Centre for Quantum Dynamics.

“Much like our everyday computer, the brains of a quantum computer consist of chains of logic gates, although quantum logic gates harness quantum phenomena.”

Modified NWChem Code Utilizes Supercomputer Parallelization

Quicker time to discovery. That’s what scientists focused on quantum chemistry are looking for. According to Bert de Jong, Computational Chemistry, Materials and Climate Group Lead, Computational Research Division, Lawrence Berkeley National Lab (LBNL), “I’m a computational chemist working extensively with experimentalists doing interdisciplinary research. To shorten time to scientific discovery, I need to be able to run simulations at near-real-time, or at least overnight, to drive or guide the next experiments.” Changes must be made in the HPC software used in quantum chemistry research to take advantage of advanced HPC systems to meet the research needs of scientists both today and in the future.

NWChem is a widely used open source software computational chemistry package that includes both quantum chemical and molecular dynamics functionality. The NWChem project started around the mid-1990s, and the code was designed from the beginning to take advantage of parallel computer systems. NWChem is actively developed by a consortium of developers and maintained by the Environmental Molecular Sciences Laboratory (EMSL) located at the Pacific Northwest National Laboratory (PNNL) in Washington State. NWChem aims to provide its users with computational chemistry tools that are scalable both in their ability to treat large scientific computational chemistry problems efficiently, and in their use of available parallel computing resources from high-performance parallel supercomputers to conventional workstation clusters.

“Rapid evolution of the computational hardware also requires significant effort geared toward the modernization of the code to meet current research needs,” states Karol Kowalski, Capability Lead for NWChem Development at PNNL.

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