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Energy and bandwidth efficiency optimization of quantum-enabled optical communication channels
We present a systematic study of quantum receivers and modulation methods enabling resource efficient quantum-enhanced optical communication. We...
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6 Quantum Tomography from Incomplete Data via MaxEnt Principle
We show how the maximum entropy (MaxEnt) principle can be efficiently used for a reconstruction of states of quantum systems from incomplete...
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On the learnability of quantum state fidelity
Current quantum processing technology is generally noisy with a limited number of qubits, stressing the importance of quantum state fidelity...
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Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe
Quantum optimal control, a toolbox for devising and implementing the shapes of external fields that accomplish given tasks in the operation of a...
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Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics
Sampling from known probability distributions is a ubiquitous task in computational science, underlying calculations in domains from linguistics to...
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A neural network assisted 171Yb+ quantum magnetometer
A versatile magnetometer must deliver a readable response when exposed to target fields in a wide range of parameters. In this work, we...
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Machine learning aided carrier recovery in continuous-variable quantum key distribution
The secret key rate of a continuous-variable quantum key distribution (CV-QKD) system is limited by excess noise. A key issue typical to all modern...
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Roots of quantum computing supremacy: superposition, entanglement, or complementarity?
The recent claim of Google to have brought forth a breakthrough in quantum computing represents a major impetus to further analyze the foundations...
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7 Experimental Quantum State Tomography of Optical Fields and Ultrafast Statistical Sampling
We review experimental work on the measurement of the quantum state of optical fields, and the relevant theoretical background. The basic technique...
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Probabilistic morphisms and Bayesian nonparametrics
In this paper we develop a functorial language of probabilistic morphisms and apply it to some basic problems in Bayesian nonparametrics. First we...
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Securing the objectivity of relative facts in the quantum world
This paper compares and contrasts relational quantum mechanics (RQM) with a pragmatist view of quantum theory (DP). I first explain important points...
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Fluorescence resonance energy transfer at the single-molecule level
Fluorescence resonance energy transfer (FRET) is a powerful spectroscopic method for measuring distances in the 2–8 nm range. Often, conformational...
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Extensive studies of the neutron star equation of state from the deep learning inference with the observational data augmentation
We discuss deep learning inference for the neutron star equation of state (EoS) using the real observational data of the mass and the radius. We make...
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Adaptive quantum state tomography with neural networks
Current algorithms for quantum state tomography (QST) are costly both on the experimental front, requiring measurement of many copies of the state,...
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Application of Bayesian statistics to the sector of decay constants in three-flavour \(\chi \)PT
The sector of decay constants of the octet of light pseudoscalar mesons in the framework of ‘resummed’ SU (3) chiral perturbation theory is...
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Interplay between Swampland and Bayesian Machine Learning in constraining cosmological models
Constraints on a dark energy dominated Universe are obtained from an interplay Bayesian (Probabilistic) Machine Learning and string Swampland...
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Models in quantum computing: a systematic review
Quantum computing is computing beyond classical computing based on quantum phenomena such as superposition and entanglement. While quantum computing...
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Quantum tomography benchmarking
Recent advances in quantum computers and simulators are steadily leading us toward full-scale quantum computing devices. Due to the fact that...
