Experimental optimal discrimination of $N$ states of a qubit with fixed rates of inconclusive outcomes
- URL: http://arxiv.org/abs/2411.14537v1
- Date: Thu, 21 Nov 2024 19:09:58 GMT
- Title: Experimental optimal discrimination of $N$ states of a qubit with fixed rates of inconclusive outcomes
- Authors: L. F. Melo, M. A. Solís-Prosser, O. Jiménez, A. Delgado, L. Neves,
- Abstract summary: In a general optimized measurement scheme, the error rate is minimized under the constraint of a fixed rate of inconclusive outcomes (FRIO)
Here, we experimentally demonstrate the optimal FRIO discrimination between $N=2,3,5,$ and $7$ equally likely symmetric states of a qubit encoded in photonic path modes.
- Score: 0.5452584641316628
- License:
- Abstract: In a general optimized measurement scheme for discriminating between nonorthogonal quantum states, the error rate is minimized under the constraint of a fixed rate of inconclusive outcomes (FRIO). This so-called optimal FRIO measurement encompasses the standard and well known minimum-error and optimal unambiguous (or maximum-confidence) discrimination strategies as particular cases. Here, we experimentally demonstrate the optimal FRIO discrimination between $N=2,3,5,$ and $7$ equally likely symmetric states of a qubit encoded in photonic path modes. Our implementation consists of applying a probabilistic quantum map which increases the distinguishability between the inputs in a controlled way, followed by a minimum-error measurement on the successfully transformed outputs. The results obtained corroborate this two-step approach and, in our experimental scheme, it can be straightforwardly extended to higher dimensions. The optimized measurement demonstrated here will be useful for quantum communication scenarios where the error rate and the inconclusive rate must be kept below the levels provided by the respective standard strategies.
Related papers
- Asymptotically Unbiased Instance-wise Regularized Partial AUC
Optimization: Theory and Algorithm [101.44676036551537]
One-way Partial AUC (OPAUC) and Two-way Partial AUC (TPAUC) measures the average performance of a binary classifier.
Most of the existing methods could only optimize PAUC approximately, leading to inevitable biases that are not controllable.
We present a simpler reformulation of the PAUC problem via distributional robust optimization AUC.
arXiv Detail & Related papers (2022-10-08T08:26:22Z) - Demonstration of optimal non-projective measurement of binary coherent
states with photon counting [0.0]
We experimentally demonstrate the optimal inconclusive measurement for the discrimination of binary coherent states.
As a particular case, we use this general measurement to implement the optimal minimum error measurement for phase-coherent states.
arXiv Detail & Related papers (2022-07-25T14:35:16Z) - Experimental quantum state discrimination using the optimal fixed rate
of inconclusive outcomes strategy [0.0]
We experimentally investigate the strategy for the optimal discrimination of two non-orthogonal states considering a fixed rate of inconclusive outcomes (FRIO)
We present a versatile experimental scheme that performs the optimal FRIO measurement for any pair of generated non-orthogonal states with arbitrary a priori probabilities and for any fixed rate of inconclusive outcomes.
arXiv Detail & Related papers (2022-04-14T01:18:50Z) - Experimentally determining the incompatibility of two qubit measurements [55.41644538483948]
We describe and realize an experimental procedure for assessing the incompatibility of two qubit measurements.
We demonstrate this fact in an optical setup, where the qubit states are encoded into the photons' polarization degrees of freedom.
arXiv Detail & Related papers (2021-12-15T19:01:44Z) - Near-optimal inference in adaptive linear regression [60.08422051718195]
Even simple methods like least squares can exhibit non-normal behavior when data is collected in an adaptive manner.
We propose a family of online debiasing estimators to correct these distributional anomalies in at least squares estimation.
We demonstrate the usefulness of our theory via applications to multi-armed bandit, autoregressive time series estimation, and active learning with exploration.
arXiv Detail & Related papers (2021-07-05T21:05:11Z) - Optimal Adaptive Strategies for Sequential Quantum Hypothesis Testing [87.17253904965372]
We consider sequential hypothesis testing between two quantum states using adaptive and non-adaptive strategies.
We show that these errors decrease exponentially with decay rates given by the measured relative entropies between the two states.
arXiv Detail & Related papers (2021-04-30T00:52:48Z) - Amortized Conditional Normalized Maximum Likelihood: Reliable Out of
Distribution Uncertainty Estimation [99.92568326314667]
We propose the amortized conditional normalized maximum likelihood (ACNML) method as a scalable general-purpose approach for uncertainty estimation.
Our algorithm builds on the conditional normalized maximum likelihood (CNML) coding scheme, which has minimax optimal properties according to the minimum description length principle.
We demonstrate that ACNML compares favorably to a number of prior techniques for uncertainty estimation in terms of calibration on out-of-distribution inputs.
arXiv Detail & Related papers (2020-11-05T08:04:34Z) - Ultimate limits of approximate unambiguous discrimination [1.14219428942199]
Two main strategies have been widely adopted: in a minimum error discrimination strategy, the average error probability is minimized; while in an unambiguous discrimination strategy, an inconclusive decision is allowed to vanish any possibility of errors when a conclusive result is obtained.
In this paper, we formulate an approximate unambiguous discrimination scenario, and derive the ultimate limits of the performance for both states and channels.
For the special class of teleportation-covariant' channels, the lower bound is achievable with maximum entangled inputs and no adaptive strategy is necessary.
arXiv Detail & Related papers (2020-10-29T16:58:42Z) - Discrimination of Ohmic thermal baths by quantum dephasing probes [68.8204255655161]
We evaluate the minimum error probability achievable by three different kinds of quantum probes, namely a qubit, a qutrit and a quantum register made of two qubits.
A qutrit probe outperforms a qubit one in the discrimination task, whereas a register made of two qubits does not offer any advantage.
arXiv Detail & Related papers (2020-08-06T08:51:51Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.