6 citations
- Saint Louis UniversityUS4 papers
- University of MichiganUS3 papers
- Palacký University OlomoucCZ2 papers
- RIKENJP2 papers
- University of Central FloridaUS2 papers
- Basque Center for Applied MathematicsES1 paper
- Bilkent UniversityTR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Computing CenterRU1 paper
- George Washington UniversityUS1 paper
- Humboldt-Universität zu BerlinDE1 paper
- Institute of Space SciencesES1 paper
7 papers · 1 filter
-like phase transitions from square roots of supersymmetric Hamiltonians
Jacob L. Barnett, Ramy El-Ganainy
We introduce a general framework for realizing -like phase transitions in non-Hermitian systems without imposing explicit parity--time () symmetry. The…
Exceptional Points and Lasing Thresholds: When Lower-Q Modes Win
Julius Kullig, Qi Zhong, Jan Wiersig +1
One of the most fundamental questions in laser physics is the following: Which mode of an optical cavity will reach the lasing threshold first when gain is applied? Intuitively, th…
Non-Hermitian topological filters
Vinzenz Zimmermann, Amin Hashemi, Kurt Busch +2
We introduce a non-Hermitian photonic filter that harnesses dissipation to selectively isolate a desired topological state. In science and engineering, dissipation is often used to…
Exploring Nonreciprocal Noise Transfer under Onsager-Casimir Symmetry in Synthetic-Field Optomechanics
Beyza Sütlüoğlu Ege, Şahin K. Özdemir, Ceyhun Bulutay
An optomechanical system of fundamental importance consists of two intercoupled mechanical resonators, which are radiation-pressure coupled individually to a photonic cavity. This…
Achieving the Quantum Fisher Information Bound in Pseudo-Hermitian Sensors
Ievgen I. Arkhipov, Franco Nori, Şahin K. Özdemir
Non-Hermitian systems have attracted considerable interest over the last few decades due to their unique spectral and dynamical properties not encountered in Hermitian counterparts…
Nonmonotone Spectral Analysis for Variational Inclusions
Oday Hazaimah
Gradient descent algorithms perform well in convex optimization but can get tied for finding local minima in non-convex optimization. A robust method that combines a spectral appro…