Academic Research

Context: The most advanced optical quantum clocks based on trapped ions are attaining a relative frequency accuracy of 10-18 and thus facilitate sensitive tests of fundamental theories of physics and searches for new unknown physics. Deviations from known physics (like the Standard Model of particle physics) might show up as a time variation of fundamental constants (like the fine-structure constant or the electron-proton mass ratio), so a precise measurement of the transition frequencies in ions (and other particles) could point to temporal or spatial variations of these constants.
In this context, a variation of the fine-structure constant is particularly interesting since it can be linked to models of ultra-light dark matter.
Activities in the group of Prof. Cigdem Issever at HU: The research group prepares the setup of a novel highly charged ion (HCI) clock that will utilize an HCI species with a high susceptibility to a variation of the fine-structure constant. The generated HCI is stored in a linear Paul trap and cooled and interrogated with the help of lasers and suitable control schemes (like quantum logic spectroscopy). Any time dependence of the frequency of the HCI’s clock transition is probed by a comparison with remote clocks for which no (or a different) variation of the fine-structure constant is expected. In parallel to this experimental work, the group studies with the help of Monte Carlo simulations how ultra-light dark matter can be detected or constrained by an entire network of optical atomic clocks.

Experimental setup for the internship project:
While the HCI clock is still in a preparatory phase, aspects of the time-dependent comparison of the frequencies of spatially separated clocks are already exercised with an existing laboratory setup. This setup will be used for the internship project; it has been built by two PhD students and comprises an optical table with a clock transfer laser (at 1550 nm), which is sent through optical fibers (non-polarization maintaining single-mode fiber) with a length of 0.1 km to a few 10 km. A fully fiber-based interferometric correction scheme (Michelson type) is applied to suppress phase noise generated on the fiber; in this way, the transfer of the laser signal through the fiber is stabilized and allows an accurate comparison of clocks connected by such (or even longer) fibers. For optimization purposes, a combined OTDR (Optical Time Domain Reflectometry) and DST (Distributed Temperature Sensing) system is used to examine the properties of the fiber under test. Both the OTDR and the DTS system are based on sending short pulses of laser light (a few ns to s) down the fiber under test and detecting the time-dependence of the back-scattered light. The analysis of back-scattered light (Rayleigh and Raman scattering) allows one to locate excessive absorption or reflection (OTDR) and the temperature (DTS) along the fiber, respectively.

Scope of the internship project: The internship will consist of two phases. In the first phase, the intern will become acquainted with the scope and the aims of the HCI clock project. Activities will comprise the reading of relevant literature and, optionally, experimenting with an existing Paul trap; this particular Paul trap exists at the Physics Department and is available for the education of Bachelor students. There is also the option to develop a Monte Carlo simulation (e.g., in Python) that generates mock clock data and translates them into constraints on the coupling of scalar ultra-light dark matter
particles. In the second phase, the intern will work with the experimental setup
described earlier. This experimental work might aid in the automation of the acquisition of test data using ARTIQ (see https://m-labs.hk/experiment-control/artiq/), a control system for quantum information experiments that is based on FPGAs but can be programmed in Python. The intern will also have the chance to analyze and understand the data recorded by the phase-noise cancellation setup and the combined OTDR/DTS.

Advanced undergraduate students (from second year) 

Master's students 

Ph.D. students 

Studies in a field related to the project.
Experience in working with Python.