Quantum Computing

Controlling Quantum Randomness From A Vacuum

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Insider Summary

  • A team of MIT researchers demonstrated the control of quantum randomness for the first time.
  • The team focused on a unique feature of quantum physics known as vacuum fluctuations.
  • By injecting a weak laser bias into an optical parametric oscillator, an optical system that naturally generates random numbers can serve as a source of controllable biased quantum randomness.

PERS CONFERENCE – A research team from the Massachusetts Institute of Technology has reached a milestone in quantum technology, demonstrating for the first time the control of quantum randomness.

The research team focused on a unique feature of quantum physics known as “vacuum fluctuations”. You might think of the vacuum as a completely empty space devoid of matter or light. However, in the quantum world, even this “empty” space is subject to fluctuations or changes.

Imagine a calm sea that suddenly waves – similar to what happens in space at the quantum level. Previously, these fluctuations allowed scientists to generate random numbers. They are also responsible for many of the interesting phenomena that quantum scientists have discovered over the last hundred years.

The findings are described today in the journal Science, in a paper led by MIT postdoctoral fellows Charles Roques-Carmes and Yannick Salamin; MIT professors Marin Soljacic and John Joannopoulos; and coworkers.

Conventionally, computers function in a deterministic way, executing step-by-step instructions that follow a predetermined set of rules and algorithms. In this paradigm, if you run the same operation multiple times, you always get the exact same result. This deterministic approach has underpinned our digital age, but it has limitations, especially when it comes to simulating the physical world or optimizing complex systems, tasks that often involve a great deal of uncertainty and randomness.

This is where the concept of probabilistic computing comes into play. Probabilistic computing systems take advantage of the intrinsic randomness of certain processes to perform computations. They don’t just give one “correct” answer, but rather a series of possible outcomes each with an associated probability. This inherently makes them well suited for simulating physical phenomena and tackling optimization problems where multiple solutions can exist and where exploration of multiple possibilities can lead to better solutions.

However, the practical implementation of probabilistic computing has historically been hampered by a significant obstacle: the lack of control over the probability distribution associated with quantum randomness. But research conducted by the MIT team has shed light on a possible solution.

In particular, the researchers have shown that injecting a weak laser “bias” into an optical parametric oscillator, an optical system that naturally generates random numbers, can serve as a source of controllable “biased” quantum randomness.

“Despite extensive studies of these quantum systems, the influence of very weak refractive fields has not been explored,” said Charles Roques-Carmes, a researcher on the research. “Our discovery of controllable quantum randomness not only allows us to revisit decades of concepts in quantum optics but also unlocks potential in probabilistic computing and high-precision field sensing.”

The team has successfully demonstrated the ability to manipulate the probabilities associated with the output state of an optical parametric oscillator, thus creating the first controllable photonic probabilistic bit (p-bit). In addition, the system has demonstrated sensitivity to temporal oscillations of bias field pulses, even well below the single-photon level.

Yannick Salamin, another member of the team, states, “Our current photonic p-bit generation system allows the production of 10,000 bits per second, each of which can follow an arbitrary binomial distribution. We hope that this technology will progress in the next few years, leading to higher levels of photonic p-bits and wider applications.”

MIT Professor Marin Soljacic emphasizes the wider implications of this work: “By making vacuum fluctuations a controllable element, we push the boundaries of what is possible in quantum-enhanced probabilistic computing. The prospect of simulating complex dynamics in fields such as combinatorial optimization and lattice quantum chromodynamics simulation is very exciting.”

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