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Super-resolution imaging has transformed scientific disciplines, from molecular biology to astronomy, by enabling visualization beyond the diffraction limit. However, current super-resolution methods require extensive calibration for each imaging setup, restricting their applicability. Our latest research introduces a novel AI-driven, device-agnostic
Milé kolegyne, milí kolegovia, dovoľte mi pozvať vás na sériu fyzikálnych prednášok, ktorá sa uskutoční 3. 1. 2025 na Ústave fyziky materiálov AV ČR v Brne. Okrem ďalších zaujímavých pozvaných rečníkov, tentokrát zavíta i Dr. Pavel Hrmo z ETH v Curychu s prednáškou
In her work, Rebeka Zrníková focused on the experimental implementation of digital holographic microscopy for live cell observation and the analysis of reconstructed images. Aleš Marák developed deep neural networks capable of quantifying key features of quantum states directly from
Adding Photons Without the Noise — Our team has made a significant breakthrough by experimentally preparing multiphoton-added coherent states of light, a key development in optical quantum state engineering. The findings, published in npj Quantum Information, highlight demonstrating the addition
Our student, Dominik Vašinka, has been awarded the prestigious Werner von Siemens Award 2023 for his Master thesis and advancement of quantum control through artificial intelligence. His innovative approach tackles the longstanding challenge of optimal control for a variety of
Our recent result demonstrates an ultra-fast multi-channel coincidence counting unit with full channel-number resolution, which meets the requirements of cutting-edge photonic experiments.
Dominik Koutný presented a talk on Deep learning of quantum entanglement as part of the Hot Topics Session at the POM23 Photonics Meetup. For more details see published paper: 10.1126/sciadv.add7131. We also presented a number of posters: R. Stárek, M.
We are thrilled to share our research on the quantification of quantum entanglement using artificial neural networks. Our approach allows us to accurately measure entanglement without requiring complete knowledge of the quantum state. By leveraging neural networks, we achieve a
Anežka and Filip defended their Master theses with distinction. Congratulations!
Our research revealed anomalous nonlinear effects in single-photon detectors, challenging established theories. Understanding and fully characterizing these effects will significantly enhance measurement accuracy in various scientific and technological applications. The results were published in Applied Physics Reviews. The preprint is