Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Conference on Lasers and Electro-Optics

On the Optimal Choice of States for Process Tomography

Lee A. Rozema, Ardavan Darabi, Dylan H. Mahler, Robin Blume-Kohout, Aephraim M. Steinberg

Published Jan 1, 2011• 0 citations
Publisher

Abstract

Quantum process tomography requires a set of input states sensitive to the unknown process. We experimentally generate a class of 4-photon states and compare their sensitivity to that of coherent states to a decohering process.
DOI
10.1364/qels.2011.qtho1

Related papers

Experimental realization of self-guided quantum process tomography

Zhibo Hou, Jun-Feng Tang, Christopher Ferrie +3 more

Characterization of quantum processes is a preliminary step necessary in the development of quantum technology. The conventional method uses standard quantum process tomography, which requires ${d}^{2}$ input states and ${d}^{4}$ quantum measurements for a $d$-dimensional Hilbert space. These experimental requirements are compounded by the complexity of processing the collected data, which can take several orders of magnitude longer than the experiment itself. In this paper we propose an alternative self-guided algorithm for quantum process tomography, tuned for the task of finding an unknown unitary process. Our algorithm is a fully automated and adaptive process characterization technique. The advantages of our algorithm are the following: it has an inherent robustness to both statistical and technical noise; it requires less space and time since there is no postprocessing of the data; it requires only a single input state and measurement; and it provides on-the-fly diagnostic information while the experiment is running. Numerical results show our algorithm achieves the same $1/n$ scaling as standard quantum process tomography when $n$ uses of the unknown process are used. We also present experimental results wherein the algorithm and its advantages are realized for the task of finding an element of SU(2).

arXiv:1908.01082•Physical Review A•Feb 18, 2020•25 citations

Quantum-Enhanced Precision in Unitary Process Tomography

Rebecca Whittaker, Xiaoqi Zhou, Hugo V. Cable +3 more

A novel scheme for unitary quantum process tomography (QPT) is theoretically presented and implemented experimentally. Multi-photon input states are used to obtain quantum-enhanced precision for the unitary estimation. Our results are compared to standard QPT.

•Jan 1, 2014•0 citations

Quantum process tomography with coherent states

Saleh Rahimi-Keshari, Artur Scherer, A. Mann +3 more

We have developed an enhanced technique for characterizing quantum optical processes based on probing unknown quantum processes only with coherent states. Our method substantially improves the original proposal (Lobino et al 2008 Science 322 563), which uses a filtered Glauber–Sudarshan decomposition to determine the effect of the process on an arbitrary state. We introduce a new relation between the action of a general quantum process on coherent state inputs and its action on an arbitrary quantum state. This relation eliminates the need to invoke the Glauber–Sudarshan representation for states; hence, it dramatically simplifies the task of process identification and removes a potential source of error. The new relation also enables straightforward extensions of the method to multi-mode and non-trace-preserving processes. We illustrate our formalism with several examples, in which we derive analytic representations of several fundamental quantum optical processes in the Fock basis. In particular, we introduce photon-number cutoff as a reasonable physical resource limitation and address resource versus accuracy trade-off in practical applications. We show that the accuracy of process estimation scales inversely with the square root of photon-number cutoff.

arXiv:1009.3307•New Journal of Physics•Jan 11, 2011•76 citations

The Blind Version of Quantum Process Tomography: Operating with Unknown Input Values

Yannick Deville, Alain Deville

System identification and inversion are two closely related problems, which lead to various configurations. In the quantum framework, system identification was only studied in the non-blind (or supervised) mode, i.e. with known input states (in addition to known output states). It is then called quantum process tomography. We here develop its blind (or unsupervised) version, operating with unknown (unentangled) input states (which are here not controlled by an automated loop). Our approach takes advantage of the blind quantum source separation (i.e. blind multi-qubit system inversion) methods based on disentanglement that we recently introduced. It is detailed for Heisenberg spin coupling and could be extended to other classes of processes. It estimates the parameter values of the Heisenberg Hamiltonian.

IFAC-PapersOnLine•Jul 1, 2017•9 citations

Efficient tomography of quantum processes

Xiang‐Bin Wang, Jiaqi Hu, Zong‐Wen Yu +1 more

We show with explicit formulas that one can completely identify an unknown quantum process with only one weakly entangled state; and identify a quantum optical Gaussian process with either one two-mode squeezed state or a few different coherent states. In tomography of a multi-mode process, our method reduces the number of different test states exponentially compared with existing methods.

arXiv:1010.0472•Oct 4, 2010•0 citations

Holistic Quantum State and Process Tomography

Nicolás Quesada, Agata M. Brańczyk, Daniel F. V. James

Incompletely characterized processes can be used for state tomography. We formalize this idea and show how to chose processes that ensure invertibility for the unknown state, as well as the unknown process parameters.

Frontiers in Optics•Jan 1, 2013•1 citation
Characterization of quantum processes is a preliminary step necessary in the development of quantum technology. The conventional method uses standard quantum process tomography, which requires d2{d}^{2}d2 input states and d4{d}^{4}d4 quantum measurements for a ddd-dimensional Hilbert space. These experimental requirements are compounded by the complexity of processing the collected data, which can take several orders of magnitude longer than the experiment itself. In this paper we propose an alternative self-guided algorithm for quantum process tomography, tuned for the task of finding an unknown unitary process. Our algorithm is a fully automated and adaptive process characterization technique. The advantages of our algorithm are the following: it has an inherent robustness to both statistical and technical noise; it requires less space and time since there is no postprocessing of the data; it requires only a single input state and measurement; and it provides on-the-fly diagnostic information while the experiment is running. Numerical results show our algorithm achieves the same 1/n1/n1/n scaling as standard quantum process tomography when nnn uses of the unknown process are used. We also present experimental results wherein the algorithm and its advantages are realized for the task of finding an element of SU(2).
We have developed an enhanced technique for characterizing quantum optical processes based on probing unknown quantum processes only with coherent states. Our method substantially improves the original proposal (Lobino et al 2008 Science 322 563), which uses a filtered Glauber–Sudarshan decomposition to determine the effect of the process on an arbitrary state. We introduce a new relation between the action of a general quantum process on coherent state inputs and its action on an arbitrary quantum state. This relation eliminates the need to invoke the Glauber–Sudarshan representation for states; hence, it dramatically simplifies the task of process identification and removes a potential source of error. The new relation also enables straightforward extensions of the method to multi-mode and non-trace-preserving processes. We illustrate our formalism with several examples, in which we derive analytic representations of several fundamental quantum optical processes in the Fock basis. In particular, we introduce photon-number cutoff as a reasonable physical resource limitation and address resource versus accuracy trade-off in practical applications. We show that the accuracy of process estimation scales inversely with the square root of photon-number cutoff.
System identification and inversion are two closely related problems, which lead to various configurations. In the quantum framework, system identification was only studied in the non-blind (or supervised) mode, i.e. with known input states (in addition to known output states). It is then called quantum process tomography. We here develop its blind (or unsupervised) version, operating with unknown (unentangled) input states (which are here not controlled by an automated loop). Our approach takes advantage of the blind quantum source separation (i.e. blind multi-qubit system inversion) methods based on disentanglement that we recently introduced. It is detailed for Heisenberg spin coupling and could be extended to other classes of processes. It estimates the parameter values of the Heisenberg Hamiltonian.