JILA Associate Fellow and University of Colorado Boulder Physics Assistant Professor Shuo Sun, along with Assistant Professor of Chemistry Andrés Montoya-Castillo and their team, have developed a new method to better understand and control “noise” in quantum technology. This noise can disrupt the quantum states of qubits, the fundamental units of quantum information. The team’s method, called Fourier Transform Noise Spectroscopy (FTNS), uses a mathematical technique to analyze the noise affecting qubits. This could lead to significant advancements in quantum computing, sensing, and control. The research was recently published in the journal npj Quantum Information.
Understanding Quantum Noise and Its Impact on Qubits
Quantum technology and quantum sensing face a significant challenge in the form of “noise” – random environmental disturbances that can disrupt the delicate quantum states of qubits, the fundamental units of quantum information. This noise can be caused by minor fluctuations in room temperature, floor vibration, or inherent instability in the qubit system. Such disturbances can disrupt a qubit’s coherence, causing it to lose its quantum state in a process known as decoherence.
The sensitivity of qubits to fluctuations in the surrounding fields and their interaction with each other pose a practical limitation to the implementation of quantum technologies on a larger scale with higher sensitivity. The noise not only affects the measurements of fragile systems like an ultra-precise quantum sensor but also makes the system less manageable.
Understanding the sources of this noise and finding ways to mitigate it is crucial for developing reliable quantum devices, such as quantum computers or sensors. The noise environment of a qubit is not only important for noise mitigation but also serves as a valuable probe for materials. In this case, the qubit acts as a sensor, providing insights into the behavior of the surrounding material environment.
Traditional Methods of Noise Characterization
To study and control this noise, scientists have traditionally used a method called Dynamical Decoupling Noise Spectroscopy (DDNS). This method involves applying precise pulses to the qubits and observing how they respond. DDNS was originally used for making the coherence times longer in qubits. It was later repurposed as a noise spectroscopy method to measure and characterize the noise among the qubits.
However, DDNS is complex and requires applying a large number of almost instantaneous laser pulses. It also makes several assumptions about the underlying noise processes, making it cumbersome and less practical for widespread use. The DDNS method has minimum and maximum frequency limits for noise spectrum reconstruction due to physical constraints, potentially causing someone to miss interesting phenomena.
A New Approach to Noise Mapping
In response to the challenges of DDNS, a new method was proposed that required fewer laser pulses and utilized a mathematical technique known as the Fourier transform. This new method, Fourier Transform Noise Spectroscopy (FTNS), offers a straightforward yet powerful way to analyze the noise affecting qubits by focusing on the qubits’ coherence dynamics.
Coherence measures how well a qubit maintains its quantum state, which is critical for its performance in quantum computations. These measurements are typically done through simple experiments like Free Induction Decay (FID) or Spin Echo, which start the qubit in a specific initial state and let its coherence decay freely over time, with zero or one intermediate pulses applied during the decay, respectively.
The Power of Fourier Transform in Noise Analysis
Once these time-based measurements are collected, the data is treated using the Fourier transform. This process is like breaking down a painting into its basic colors to understand what it is made of. The Fourier transform is used to convert the time-domain data into frequency-domain data, effectively breaking down the complex signal into its constituent frequencies.
By doing so, FTNS revealed the noise spectrum, showing which noise frequencies were present and how strong they were. The FTNS method also handled various types of noise, including complex noise patterns that were challenging for other methods like DDNS to decipher.
While FTNS has some limitations, like minimum and maximum frequency constraints and the need for high-resolution time and coherence measurements, these limitations are far less constraining than DDNS’s.
Future Applications and Research
The FTNS method is currently being tested experimentally in nitrogen-vacancy centers, often found within diamonds used as qubits. Simultaneously, efforts are being made to implement FTNS in molecular qubits and magnets. The ability of the FTNS method to reveal the frequency-resolved conversation between a qubit or sensor and its environment opens up new opportunities in the field of quantum sensing.
This could enable imaging of complex biological processes, like protein folding, with unprecedented detail and temporal resolution. The research, funded by several grants from the National Science Foundation and the Sloan Research Fellowship, holds promise for significant advancements in quantum computing, sensing, and control.
External Link: Click Here For More
