Related papers: Accuracy of the quantum regression theorem for pho…
We report an experiment that demonstrates full function of a quantum router using entangled photons, where the paths of a single-photon pulse are controlled in a coherent fashion by polarization of another single photon. Through a…
Quantum reservoir computing (QRC) is a hardware-implementation-friendly quantum neural network scheme with minimal physical system requirements and a proven advantage over classical counterparts. We use an extension of the positive-P phase…
We propose to use neural networks to estimate the rates of coherent and incoherent processes in quantum systems from continuous measurement records. In particular, we adapt an image recognition algorithm to recognize the patterns in…
Two descriptions are introduced and analyzed for a reflectivity estimation and detection scheme that does not involve measurement of photons scattered by the target. One description, provided by the Hamiltonian dynamics of the full…
Quantile Regression (QR) can be used to estimate aleatoric uncertainty in deep neural networks and can generate prediction intervals. Quantifying uncertainty is particularly important in critical applications such as clinical diagnosis,…
A quantum trajectory describes the evolution of a quantum system undergoing indirect measurement. In the discrete-time setting, the state of the system is updated by applying Kraus operators according to the measurement results. From an…
This study proposes a Quantum Fourier Transform (QFT)-enhanced quantum kernel for short-term time-series forecasting. Each signal is windowed, amplitude-encoded, transformed by a QFT, then passed through a protective rotation layer to avoid…
We give an algorithm for prediction on a quantum computer which is based on a linear regression model with least squares optimisation. Opposed to related previous contributions suffering from the problem of reading out the optimal…
Quantum theory (QT) provides statistical predictions for various physical phenomena. The outcomes of these measurements are in general some numerical time series registered by some macroscopic instruments. The various empirical probability…
The observation of quantum dot resonance fluorescence enabled a new solid-state approach to generating single photons with a bandwidth almost as narrow as the natural linewidth of a quantum dot transition. Here, we operate in the Heitler…
Quantum detection processes in QFT must play a key role in the description of quantum field correlations, such as the appearance of entanglement, and of causal effects. We consider the detection in the case of a simple QFT model with a…
Fault-tolerant quantum computing requires gates which function correctly despite the presence of errors, and are scalable if the error probability-per-gate is below a threshold value. To date, no method has been described for calculating…
Quantile Regression (QR) provides a way to approximate a single conditional quantile. To have a more informative description of the conditional distribution, QR can be merged with deep learning techniques to simultaneously estimate multiple…
Compton scattering is one of the cornerstones of quantum physics, describing the fundamental interaction of a charged particle with photons. The Compton effect and its inverse are utilized in experiments driving free electrons by high…
Quantum sensing with undetected photons is a technique where photons of one wavelength probe a sample, but information is extracted by measuring photons of another wavelength that never interacts with the sample. This has seen significant…
We present measurements on a quantum dot and a nearby, capacitively coupled, quantum point contact used as a charge detector. With the dot being weakly coupled to only a single reservoir, the transfer of individual electrons onto and off…
In this work we investigate quantum-enhanced target detection in the presence of large background noise using multidimensional quantum correlations between photon pairs generated through spontaneous parametric down-conversion. Until now…
Quantum machine learning algorithms have very recently attracted significant attention in photonic platforms. In particular, reconfigurable integrated photonic circuits offer a promising route, thanks to the possibility of implementing…
Single-photon routers in cavity and circuit QED direct photons by the qubit's energy eigenstate -- a projective decision that destroys coherence. We propose a different primitive: coherence-gated routing, where the decision depends on the…
Quantum geometric tensor (QGT), including a symmetric real part defined as quantum metric and an antisymmetric part defined as Berry curvature, is essential for understanding many phenomena. We studied the photogalvanic effect of a…