Scientists demonstrate control over quantum randomness using laser bias

Controlling probability distribution associated with quantum randomness is a first and is fundamental to developing probabilistic computing and weak field sensing.
Tejasri Gururaj
Artistic illustration of the generation of tunable random numbers from the quantum vacuum.
Artistic illustration of the generation of tunable random numbers from the quantum vacuum.

Lei Chen 

"We can now control quantum randomness in a vacuum," claim scientists. 

It's hard to think of a vacuum, as it's a place devoid of matter or light. But in the quantum world, this isn't true. Tiny changes or fluctuations exist in a vacuum, like ripples in water. These fluctuations are in electromagnetic fields, which can produce perfect randomness. 

Scientists have previously used these fluctuations to generate random numbers. These vacuum fluctuations are also responsible for several phenomena, such as quantum tunneling, in which a quantum particle can pass through a potential energy barrier that would be classically impassable.

Now, scientists from the Massachusetts Institute of Technology (MIT) have claimed they can harness and control quantum randomness in optical systems. 

The objective of MIT postdoctoral associates Charles Roques-Carmes and Yannick Salamin, who were part of the research team, was to develop a technique for controlling the probability distributions linked to quantum randomness. This is crucial for applications like weak field sensing and probabilistic computing. 

Probabilistic computing

In the quantum world, nothing is 100 certain, so we often deal with probabilities. Randomness plays a fundamental role due to the inherent probabilistic nature of quantum particles.

In conventional or classical computers, every task is deterministic, meaning it is performed step-by-step, and the outcome remains the same each time. Although this type of computing has led to the dawn of the digital age, it has some limitations. 

Physical systems are complex and follow quantum mechanics, which involves randomness and uncertainty, which classical computers can't simulate. 

Probabilistic computing relies on statistical inference, stochastic processes, and probabilistic models to simulate and study phenomena involving randomness and in scenarios where multiple solutions exist, and exploring different possibilities can lead to better results. 

It has applications in various domains, including machine learning, artificial intelligence, data analysis, optimization, and simulation.

Practically implementing probabilistic computing has been challenging due to the inability to control the probability distributions related to quantum randomness. It means manipulating or adjusting the probabilities associated with the outcomes of quantum random processes is difficult.

Injecting bias

The MIT researchers achieved control by injecting a weak laser bias into an optical parametric oscillator or OPO, a system capable of generating random numbers. A weak laser bias refers to a low-intensity laser beam that they intentionally introduced. 

By introducing this weak laser bias, the researchers could influence the quantum system and manipulate the probabilities linked to the output states of the OPO. 

Scientists demonstrate control over quantum randomness using laser bias
Lead authors Charles Roques-Carmes (left) and Yannick Salamin (right) operating the experimental system.

Even at very weak intensities similar to the amplitude of vacuum fluctuations, the bias field enabled the researchers to move between completely random outcomes and deterministic state selection.

In simple words, the researchers demonstrated that by adjusting the attenuation level of the bias field, they could control the probabilities of the two possible output states of the optical parametric oscillator. This control over the probability distributions enabled the creation of the first-ever controllable photonic probabilistic bit or p-bit.

Additionally, the system exhibited sensitivity to the temporal oscillations of the bias field pulses, even at levels below a single photon. This sensitivity suggests that the system has the potential to detect and manipulate faint electromagnetic pulses.

By successfully injecting and manipulating the weak laser bias field, the researchers could achieve control over the probability distributions associated with quantum randomness in the optical parametric oscillator.

"Despite extensive study of these quantum systems, the influence of a very weak bias field was unexplored. Our discovery of controllable quantum randomness not only allows us to revisit decades-old concepts in quantum optics but also opens up potential in probabilistic computing and ultra-precise field sensing," said Charles Roques-Carmes in a press release.

The findings of the study are published in the journal Science.

Study abstract:

Quantum field theory suggests that electromagnetic fields naturally fluctuate, and these fluctuations can be harnessed as a source of perfect randomness. Many potential applications of randomness rely on controllable probability distributions. We show that vacuum-level bias fields injected into multistable optical systems enable a controllable source of quantum randomness, and we demonstrated this concept in an optical parametric oscillator (OPO). By injecting bias pulses with less than one photon on average, we controlled the probabilities of the two possible OPO output states. The potential of our approach for sensing sub–photon-level fields was demonstrated by reconstructing the temporal shape of fields below the single-photon level. Our results provide a platform to study quantum dynamics in nonlinear driven-dissipative systems and point toward applications in probabilistic computing and weak field sensing.

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