Quantum Computing News

Ultralight Dark Matter Detection

Superconducting qubit networks show increased sensitivity to ultralight dark matter. By improving network topology and measurement techniques, research outperforms traditional detection techniques while being compatible with existing quantum hardware. Phase shifts caused by dark matter are successfully extracted by Bayesian inference, which is resilient against local noise.

Dark matter’s elusiveness still poses a challenge to modern physics, leading to research into new detection techniques that go beyond accepted methods. A recent study describes a quantum sensor network that uses quantum entanglement and optimised measurement techniques to increase sensitivity to ultralight dark matter fluxes. In a study titled “Optimised quantum sensor networks for ultralight dark matter detection,” researchers from Tohoku University, Adriel I. Santoso (Department of Mechanical and Aerospace Engineering) and Le Bin Ho (spanning the Frontier Research Institute for Interdisciplinary Sciences and the Department of Applied Physics), share their findings. Even under actual noise settings, their work shows enhanced detection capabilities over typical quantum protocols by examining interconnected superconducting qubits placed in different network topologies.

Despite its persistent resistance to direct detection, scientists are improving methods to detect dark matter, a non-luminous material thought to make up over 85% of the stuff in the universe. To overcome the drawbacks of single-sensor methods, a recent study describes a network-based sensing architecture that makes use of superconducting qubits to increase sensitivity to ultralight dark matter fluxes.

Building networks of superconducting qubits quantum bits that exhibit superposition and entanglement and connecting them using controlled-Z gates is the fundamental component of this breakthrough. These gates allow for correlated measurements by modifying the quantum state of qubits. To ascertain which network topology maximises the possibility for signal detection, researchers experimented with linear chains, rings, star configurations, and completely linked graphs.

A variational metrology framework is used in the study to optimise the quantum state’s initial preparation as well as the measurement procedure that follows. This entails reducing the Cramer-Rao constraints, which are essential restrictions on the accuracy of parameter estimate, both quantum and classical. Scientists can explore previously unreachable areas of parameter space by carefully adjusting these parameters to find configurations that increase sensitivity to possible dark matter signals.

It is anticipated that dark matter interactions will cause minute phase shifts in the qubits’ quantum state. These phase shifts are then extracted from the measurement results using Bayesian inference, a statistical technique for updating beliefs based on evidence, offering a reliable approach for signal recovery and analysis. The findings show that well-planned network topologies perform noticeably better than traditional Greenberger-Horne-Zeilinger (GHZ)-based protocols, which are a common benchmark in quantum sensing.

This method’s practicality is one of its main advantages. Because the optimised networks preserve modest circuit depths, fewer sequential operations are needed for the quantum computations. This is important because quantum coherence is limited on the noisy intermediate-scale quantum (NISQ) hardware that is currently on the market. Additionally, the work shows resilience to local dephasing noise, which is a frequent cause of error in quantum systems brought on by interactions with the environment, guaranteeing dependable performance under realistic circumstances.

The significance of network structure in improving dark matter detection is highlighted by this study. Through the active use of entanglement and network topology optimisation, researchers show how to develop scalable methods for increasing sensitivity and opening up new avenues for the hunt for dark matter. In order to further improve sensitivity and precision, future research will concentrate on examining increasingly intricate network topologies and creating sophisticated data processing methods. Additionally proposed is integration with current astrophysical observations and direct detection investigations, which could lead to a multifaceted approach to solving the mysteries of dark matter.

Squeezer

Researchers at the University of New South Wales (UNSW) have created a tool that may help find dark matter. Through a technique known as “squeezing,” the group, under the direction of Associate Professor Jarryd Pla, developed an amplifier that can monitor weak microwave signals precisely. This method produces ultra-precise measurements of one signal attribute while lowering the uncertainty of another. Axions are hypothetical particles that have been suggested as a component of dark matter, and the gadget may expedite the hunt for them. Spectroscopy and upcoming quantum computers may also benefit from the team’s expertise.

Quantum Engineers Develop Amplifier to Aid Dark Matter Research

A group of quantum engineers from Sydney’s University of New South Wales (UNSW) have created a novel amplifier that might help researchers find elusive dark matter particles. Using a technique called “squeezing,” this apparatus measures extremely faint microwave waves precisely.

Squeezing reduces signal uncertainty to measure one aspect ultra-precisely. This method is useful in quantum mechanics, because Werner Heisenberg’s uncertainty principle prohibits simultaneous measurement of a particle’s position and velocity.

Associate Professor Jarryd Pla’s team improved microwave signal monitoring, including cell phone signals, to set a world record. Any signal’s measurement accuracy is essentially constrained by noise, or the fuzziness that obscures signals. Nevertheless, the UNSW team’s squeezer is capable of surpassing this quantum limit.

The Squeezer: A Device to Reduce Noise

In order to drastically reduce noise in another direction, or “squeeze,” the squeezer amplifies noise in one direction. Measurements become more accurate as a result of this noise reduction. In order to eliminate sources of loss, the device was the product of extensive engineering and painstaking work. In order to construct the amplifier, extremely high-quality superconducting materials were used.

As axions are infamously elusive particles that are currently just theoretical but have been suggested by many as the secret component of mysterious dark matter, the team thinks that this new technology could assist expedite the search for them.

The Hunt for Axions: A Potential Key to Dark Matter

Scientists need precise measurements to find dark matter, which accounts about 27% of the cosmos. Nothing emits or absorbs light, making dark matter “invisible.” But because it keeps galaxies from flying apart with its gravitational pull, astronomers think it must exist.

Axions are suggested to exist in one of the numerous ideas regarding the makeup of dark matter. These particles, which have never been found, are thought to be incredibly minuscule and light in mass, allowing them to interact with other known matter almost subtly. Axions should, according to one theory, emit very weak microwave signals when exposed to strong magnetic fields.

The Squeezer in Axion Detection

Measurements for axion detection may now be completed up to six times faster because to the squeezing work done at UNSW, increasing the likelihood of finding an elusive axion. Squeezers can help axion detectors measure more quickly and with less noise. The findings suggest that those tests might now be carried out even more quickly,” A/Prof. Pla explains.

Broad Applications of the Squeezer

There are other possible uses for the team’s new amplification technology outside the hunt for dark matter. The squeezer works in strong magnetic fields and at higher temperatures than previous models. This makes it suitable for spectroscopy, which studies the structure of new materials and biological systems like proteins. Squeezed noise allows you to measure samples more precisely or explore smaller volumes.

Additionally, the squeezed noise itself might find application in quantum computers in the future. It turns out that a certain kind of quantum computer can be constructed using squeezed vacuum noise. It’s exciting to note that the amount of squeezing we’ve accomplished is very close to what would be required to construct such a system, according to Dr. Anders Kringhøj, who is part of the UNSW quantum technologies team.