The exponential scaling in sample complexity which characterizes quantum tomography can be circumvented using a computational learning theory approach, reducing it to a linear one. Here we experimentally demonstrate this linear scaling in optical systems with up to 6 qubits
We propose a quantum tomography scheme for pure qudit systems which adopts a certain version of rand...
Finding optimal measurement schemes in quantum state tomography is a fundamental problem in quantum ...
Quantum state tomography is an important step in quantum information processing. For ensemble system...
The number of parameters describing a quantum state is well known to grow exponentially with the num...
The number of parameters describing a quantum state is well known to grow exponentially with the num...
The number of parameters describing a quantum state is well known to grow exponentially with the num...
The number of parameters describing a quantum state is well known to grow exponentially with the num...
Traditional quantum state tomography requires a number of measurements that grows exponentially with...
Traditional quantum state tomography requires a number of measurements that grows exponentially with...
Quantum computation - the use of quantum systems as bits, or qubits, to perform computation - has be...
Quantum computation - the use of quantum systems as bits, or qubits, to perform computation - has be...
International audienceOne of the key issue in machine learning is the characterization of the learna...
We train convolutional neural networks to predict whether or not a set of measurements is informatio...
We train convolutional neural networks to predict whether or not a set of measurements is informatio...
Recently, tremendous progress has been made in the field of quantum science and technologies: differ...
We propose a quantum tomography scheme for pure qudit systems which adopts a certain version of rand...
Finding optimal measurement schemes in quantum state tomography is a fundamental problem in quantum ...
Quantum state tomography is an important step in quantum information processing. For ensemble system...
The number of parameters describing a quantum state is well known to grow exponentially with the num...
The number of parameters describing a quantum state is well known to grow exponentially with the num...
The number of parameters describing a quantum state is well known to grow exponentially with the num...
The number of parameters describing a quantum state is well known to grow exponentially with the num...
Traditional quantum state tomography requires a number of measurements that grows exponentially with...
Traditional quantum state tomography requires a number of measurements that grows exponentially with...
Quantum computation - the use of quantum systems as bits, or qubits, to perform computation - has be...
Quantum computation - the use of quantum systems as bits, or qubits, to perform computation - has be...
International audienceOne of the key issue in machine learning is the characterization of the learna...
We train convolutional neural networks to predict whether or not a set of measurements is informatio...
We train convolutional neural networks to predict whether or not a set of measurements is informatio...
Recently, tremendous progress has been made in the field of quantum science and technologies: differ...
We propose a quantum tomography scheme for pure qudit systems which adopts a certain version of rand...
Finding optimal measurement schemes in quantum state tomography is a fundamental problem in quantum ...
Quantum state tomography is an important step in quantum information processing. For ensemble system...
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