Posted in | Quantum Physics

Quantum Vibrations of Single Molecule Captured Using Photonic Quantum Simulator

Researchers have demonstrated the ability of an optical chip to simulate the motion of atoms within molecules at the quantum level, which could open superior means for developing chemicals that are used as pharmaceuticals.

Dr Laing’s laboratory where the experiments were performed. Single photons of light are generated using a powerful Ti-Sapphire laser, to pump a series of nonlinear crystals, operated by PhD student and co-author Nicola Maraviglia (left). The single photons are collected into optical fibers and injected into the photonic chip, next to Laing (right). Inset top left is a close up of the photonic chip taken by NTT scientist and co-author, Nobuyuki Matsuda. (Credit: University of Bristol)

In an optical chip, light is used to process information, in the place of electricity, where the chip functions as a quantum computing circuit when it uses single particles of light, called photons. Data collected from the chip can be used to carry out a frame-by-frame reconstruction of atomic motions to produce a virtual movie of the quantum vibrations of a molecule, which is the core concept of the study reported in the Nature journal on May 30th, 2018.

These outcomes are the fruit of an association between scientists from the University of Bristol, MIT, IUPUI, Nokia Bell Labs, and NTT. In addition to opening the door for highly efficient pharmaceutical developments, the study could induce innovative techniques of molecular modeling for industrial chemists.

In the 1960s, when lasers were invented, experimental chemists conceptualized their use in the disintegration of molecules. However, the vibrations inside molecules instantaneously redistribute the laser energy before disintegration of the targeted molecular bond. If the behavior of molecules has to be controlled, it is necessary to gain insights into the way they vibrate at the quantum level. However, massive computational power is required to model these dynamics, even more than what is anticipated from future generations of supercomputers.

The Quantum Engineering and Technology Labs at Bristol have pioneered the application of optical chips, in which single photons of light are controlled, as the fundamental circuitry for quantum computers. It is anticipated that quantum computers will become exponentially faster when compared to traditional supercomputers in solving specific problems. However, developing a quantum computer is a highly difficult long-term goal.

As described in Nature, the researchers illustrated an innovative course to achieve molecular modeling that could turn out an early application of photonic quantum technologies. The new techniques harness an analogy between the vibrations of atoms in molecules and photons of light in optical chips.

According to Bristol physicist Dr Anthony Laing, who headed the study, “We can think of the atoms in molecules as being connected by springs. Across the whole molecule, the connected atoms will collectively vibrate, like a complicated dance routine. At a quantum level, the energy of the dance goes up or down in well-defined levels, as if the beat of the music has moved up or down a notch. Each notch represents a quantum of vibration.

Light also comes in quantised packets called photons. Mathematically, a quantum of light is like a quantum of molecular vibration. Using integrated chips, we can control the behaviour of photons very precisely. We can program a photonic chip to mimic the vibrations of a molecule.

Dr Anthony Laing

We program the chip, mapping its components to the structure of a particular molecule, say ammonia, then simulate how a particular vibrational pattern evolves over some time interval. By taking many time intervals, we essentially build up a movie of the molecular dynamics.” Dr Laing added.

Talking about the versatility of the simulator, first author Dr Chris Sparrow, who was a student on the project, stated that, “The chip can be reprogrammed in a few seconds to simulate different molecules. In these experiments we simulated the dynamics of ammonia and a type of formaldehyde, and other more exotic molecules. We simulated a water molecule reaching thermal equilibrium with its environment, and energy transport in a protein fragment.

In this type of simulation, because time is a controllable parameter, we can immediately jump to the most interesting points of the movie. Or play the simulation in slow motion. We can even rewind the simulation to understand the origins of a particular vibrational pattern.

Dr Chris Sparrow

Joint first author, Dr Enrique Martín-Lopéz, who is at present a Senior Researcher with Nokia Bell Labs, added, “We were also able to show how a machine learning algorithm can identify the type of vibration that best breaks apart an ammonia molecule. A key feature of the photonic simulator that enables this is its tracking of energy moving through the molecule, from one localised vibration to another. Developing these quantum simulation techniques further has clear industrial relevance.”

Japanese Telecoms company NTT fabricated the photonic chip used in the experiments.

Dr Laing described the main directions for the future of the study, “Scaling up the simulators to a size where they can provide an advantage over conventional computing methods will likely require error correction or error mitigation techniques. And we want to further develop the sophistication of molecular model that we use as the program for the simulator. Part of this study was to demonstrate techniques that go beyond the standard harmonic approximation of molecular dynamics. We need to push these methods to increase the real-world accuracy of our models.

This approach to quantum simulation uses analogies between photonics and molecular vibrations as a starting point. This gives us a head start in being able to implement interesting simulations. Building on this, we hope that we can realise quantum simulation and modelling tools that provide a practical advantage in the coming years.

Dr Anthony Laing

The researchers acknowledge support from the European Research Council (ERC). A.N. is thankful for support from the Wilkinson Foundation. J.C. is supported by EU H2020 Marie Sklodowska-Curie grant number 751016. Y.N.J. was supported by NSF grant number DMR-1054020. J.L.O’B. acknowledges a Royal Society Wolfson Merit Award and a Royal Academy of Engineering Chair in Emerging Technologies. A.L acknowledges a fellowship support from EPSRC.

Credit: University of Bristol

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