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Viterbi decoding of CRES signals in Project 8

by Peña, J I , Li, M , Hartse, J , Fertl, M , Gladstone, L , Kazkaz, K , LaRoque, B H , Ashtari Esfahani, A , Claessens, C , Saldaña, L , Grando, M , Novitski, E , Bogorad, Z , Slocum, P L , Oblath, N S , VanDevender, B A , Thümmler, T , Lindman, A , Sun, Y-H , Buzinsky, N , Robertson, R G H , Telles, A B , Thomas, F , Zayas, E , Johnston, J , Van De Pontseele, W , Heeger, K M , Guigue, M , Monreal, B , Matthé, C , de Viveiros, L , Formaggio, J A , Schram, M , Tvrznikova, L , Ziegler, A , Mohiuddin, R , Surukuchi, P T , Pettus, W , Jones, A M , Nikkel, J A , Böser, S , Huyan, X , Reimann, R , Thomas, M , Stachurska, J , Weiss, T E , Rybka, G , Wendler, T

in Algorithms / Charged particles / Cyclotron radiation / Cyclotrons / Frequency measurement / hidden Markov model / Instrumentation and Detectors / Markov chains / neutrino mass / Physics / Radiation / Viterbi algorithm / Viterbi algorithm detectors / Viterbi decoding

2022

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Viterbi decoding of CRES signals in Project 8

2022

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Viterbi decoding of CRES signals in Project 8

2022

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Journal Article

Viterbi decoding of CRES signals in Project 8

Peña, J I,

Li, M,

Hartse, J,

Fertl, M,

Gladstone, L,

Kazkaz, K,

LaRoque, B H,

Ashtari Esfahani, A,

Claessens, C,

Saldaña, L,

Grando, M,

Novitski, E,

Bogorad, Z,

Slocum, P L,

Oblath, N S,

VanDevender, B A,

Thümmler, T,

Lindman, A,

Sun, Y-H,

Buzinsky, N,

Robertson, R G H,

Telles, A B,

Thomas, F,

Zayas, E,

Johnston, J,

Van De Pontseele, W,

Heeger, K M,

Guigue, M,

Monreal, B,

Matthé, C,

de Viveiros, L,

Formaggio, J A,

Schram, M,

Tvrznikova, L,

Ziegler, A,

Mohiuddin, R,

Surukuchi, P T,

Pettus, W,

Jones, A M,

Nikkel, J A,

Böser, S,

Huyan, X,

Reimann, R,

Thomas, M,

Stachurska, J,

Weiss, T E,

Rybka, G,

Wendler, T

2022

Overview

Cyclotron radiation emission spectroscopy (CRES) is a modern approach for determining charged particle energies via high-precision frequency measurements of the emitted cyclotron radiation. For CRES experiments with gas within the fiducial volume, signal and noise dynamics can be modelled by a hidden Markov model. We introduce a novel application of the Viterbi algorithm in order to derive informational limits on the optimal detection of cyclotron radiation signals in this class of gas-filled CRES experiments, thereby providing concrete limits from which future reconstruction algorithms, as well as detector designs, can be constrained. The validity of the resultant decision rules is confirmed using both Monte Carlo and Project 8 data.

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Publisher

IOP Publishing,Institute of Physics: Open Access Journals

Subject

Algorithms

/ Charged particles

/ Cyclotron radiation

/ Cyclotrons

/ Frequency measurement

/ hidden Markov model

/ Instrumentation and Detectors