Simultaneous Estimation of Parameters and the State of an Optical Parametric Oscillator System

In this article, we consider the filtering problem of an optical parametric oscillator (OPO). The OPO pump power may fluctuate due to environmental disturbances, resulting in uncertainty in the system modeling. Thus, both the state and the unknown parameter may need to be estimated simultaneously. We formulate this problem using a state-space representation of the […]

Efficient Quantum Network Communication Using Optimized Entanglement Swapping Trees

Quantum network communication is challenging, as the no-cloning theorem in the quantum regime makes many classical techniques inapplicable; in particular, the direct transmission of qubit states over long distances is infeasible due to unrecoverable errors. For the long-distance communication of unknown quantum states, the only viable communication approach (assuming local operations and classical communications) is […]

Machine-Learning-Based Parameter Estimation of Gaussian Quantum States

In this article, we propose a machine-learning framework for parameter estimation of single-mode Gaussian quantum states. Under a Bayesian framework, our approach estimates parameters of suitable prior distributions from measured data. For phase-space displacement and squeezing parameter estimation, this is achieved by introducing expectation–maximization (EM)-based algorithms, while for phase parameter estimation, an empirical Bayes method […]

New Single-Preparation Methods for Unsupervised Quantum Machine Learning Problems

The term “machine learning” especially refers to algorithms that derive mappings, i.e., input–output transforms, by using numerical data that provide information about considered transforms. These transforms appear in many problems related to classification/clustering, regression, system identification, system inversion, and input signal restoration/separation. We here analyze the connections between all these problems in the classical and […]

On the Experimental Feasibility of Quantum State Reconstruction via Machine Learning

We determine the resource scaling of machine learning-based quantum state reconstruction methods, in terms of inference and training, for systems of up to four qubits when constrained to pure states. Further, we examine system performance in the low-count regime, likely to be encountered in the tomography of high-dimensional systems. Finally, we implement our quantum state […]

Efficient Discrete Feature Encoding for Variational Quantum Classifier

Recent days have witnessed significant interests in applying quantum-enhanced techniques for solving a variety of machine learning tasks. Variational methods that use quantum resources of imperfect quantum devices with the help of classical computing techniques are popular for supervised learning. Variational quantum classification (VQC) is one of such methods with possible quantum advantage in using […]

Efficient Boolean Methods for Preparing Uniform Quantum States

As each quantum algorithm requires a specific initial quantum state, quantum state preparation is an important task in quantum computing. The preparation of quantum states is performed by a quantum circuit consisting of controlled-NOT (CNOT) and single-qubit gates. Known algorithms to prepare arbitrary n -qubit quantum states create quantum circuits in O(2n) runtime and use O(2n) CNOTs, which are more expensive […]

Efficient Optimization of Cutoffs in Quantum Repeater Chains

Quantum communication enables the implementation of tasks that are unachievable with classical resources. However, losses on the communication channel preclude the direct long-distance transmission of quantum information in many relevant scenarios. In principle, quantum repeaters allow one to overcome losses. However, realistic hardware parameters make long-distance quantum communication a challenge in practice. For instance, in […]

Encoding of Nonbinary Entanglement-Unassisted and Assisted Stabilizer Codes

Quantum coding schemes over qudits using preshared entanglement between the encoder and decoder can provide better error correction capability than without it. In this article, we develop procedures for constructing encoding operators for entanglement-unassisted and entanglement-assisted qudit stabilizer codes over Fpk, with p prime and k≥1 from first principles, generalizing prior works on qubit-based codes and codes that work […]