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Kalman filtering for optimal control in inertial sensing
The project aims at the programming of a Kalman filter on a FPGA (field gate programmable array) inside a Red Pitaya. We will use the Kalman filter to estimate the state of levtiated nanoparticles used for inertial sensing.
Keywords: State estimation, Optimal control, levitation, Electronics, Inertial Sensing
We are looking for a curious and motivated master student who wants to join our young & international NSL group and explore with us the limits of real world applications of levitated nanoparticles.
**Project background:**
The versatile field of force and acceleration sensing is of great importance for both fundamental research and real world applications, as we can see daily in our mobile phones. Our international project IQLev is working on the development of inertial sensors based on levitated nanoparticles that combine the intrinsic high sensitivity of Levitodynamics with its moderate experimental effort.
In our experiments, we trap a silica nanoparticle in optical tweezers in ultrahigh vacuum and investigate its response to external accelerations by detecting its motion. In order to control the particle`s motion and extract its kinetic energy, we will apply optimal control theory where the Kalman filter plays an important role by estimating the particles trajectory nearly in real time such that this information can be used to slow down the particle.
**Project description:**
Your project aims at the programming of a Kalman filter on an FPGA (field gate programmable array) inside a Red Pitaya and its application and characterization with levitated nanoparticles. Your tasks at first will be mainly to learn how to code the Kalman filter, before you will combine it with our help into the existing experiment in the laboratory.
**Working in our group:**
We offer you close supervision through PhD and Postdocs but also expect that you work independently. In your project, you will get into contact with a multitude of technologies like optics, lasers, electronics, coding in python and Verilog, data evaluation and vacuum technology among others.
If we sparked your interest, contact us nmeyer@ethz.ch or rquidant@ethz.ch
We are looking for a curious and motivated master student who wants to join our young & international NSL group and explore with us the limits of real world applications of levitated nanoparticles.
**Project background:** The versatile field of force and acceleration sensing is of great importance for both fundamental research and real world applications, as we can see daily in our mobile phones. Our international project IQLev is working on the development of inertial sensors based on levitated nanoparticles that combine the intrinsic high sensitivity of Levitodynamics with its moderate experimental effort. In our experiments, we trap a silica nanoparticle in optical tweezers in ultrahigh vacuum and investigate its response to external accelerations by detecting its motion. In order to control the particle`s motion and extract its kinetic energy, we will apply optimal control theory where the Kalman filter plays an important role by estimating the particles trajectory nearly in real time such that this information can be used to slow down the particle.
**Project description:** Your project aims at the programming of a Kalman filter on an FPGA (field gate programmable array) inside a Red Pitaya and its application and characterization with levitated nanoparticles. Your tasks at first will be mainly to learn how to code the Kalman filter, before you will combine it with our help into the existing experiment in the laboratory.
**Working in our group:** We offer you close supervision through PhD and Postdocs but also expect that you work independently. In your project, you will get into contact with a multitude of technologies like optics, lasers, electronics, coding in python and Verilog, data evaluation and vacuum technology among others.
If we sparked your interest, contact us nmeyer@ethz.ch or rquidant@ethz.ch