Optimising the relative entropy under semi definite constraints -- A new tool for estimating key rates in QKD
- URL: http://arxiv.org/abs/2404.17016v1
- Date: Thu, 25 Apr 2024 20:19:47 GMT
- Title: Optimising the relative entropy under semi definite constraints -- A new tool for estimating key rates in QKD
- Authors: Gereon Koßmann, René Schwonnek,
- Abstract summary: Finding the minimal relative entropy of two quantum states under semi definite constraints is a pivotal problem.
We provide a method that addresses this optimisation.
We build on a recently introduced integral representation of quantum relative entropy by P.E. Frenkel.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Finding the minimal relative entropy of two quantum states under semi definite constraints is a pivotal problem located at the mathematical core of various applications in quantum information theory. In this work, we provide a method that addresses this optimisation. Our primordial motivation stems form the essential task of estimating secret key rates for QKD from the measurement statistics of a real device. Further applications include the computation of channel capacities, the estimation of entanglement measures from experimental data and many more. For all those tasks it is highly relevant to provide both, provable upper and lower bounds. An efficient method for this is the central result of this work. We build on a recently introduced integral representation of quantum relative entropy by P.E. Frenkel and provide reliable bounds as a sequence of semi definite programs (SDPs). Our approach ensures provable quadratic order convergence, while also maintaining resource efficiency in terms of SDP matrix dimensions. Additionally, we can provide gap estimates to the optimum at each iteration stage.
Related papers
- Applicability of Measurement-based Quantum Computation towards Physically-driven Variational Quantum Eigensolver [17.975555487972166]
Variational quantum algorithms are considered one of the most promising methods for obtaining near-term quantum advantages.
The roadblock to developing quantum algorithms with the measurement-based quantum computation scheme is resource cost.
We propose an efficient measurement-based quantum algorithm for quantum many-body system simulation tasks, called measurement-based Hamiltonian variational ansatz (MBHVA)
arXiv Detail & Related papers (2023-07-19T08:07:53Z) - D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory [79.50644650795012]
We propose a deep learning approach to solve Kohn-Sham Density Functional Theory (KS-DFT)
We prove that such an approach has the same expressivity as the SCF method, yet reduces the computational complexity.
In addition, we show that our approach enables us to explore more complex neural-based wave functions.
arXiv Detail & Related papers (2023-03-01T10:38:10Z) - Guaranteed efficient energy estimation of quantum many-body Hamiltonians
using ShadowGrouping [55.47824411563162]
Estimation of the energy of quantum many-body systems is a paradigmatic task in various research fields.
We aim to find the optimal strategy with single-qubit measurements that yields the highest provable accuracy given a total measurement budget.
We develop a practical, efficient estimation strategy, which we call ShadowGrouping.
arXiv Detail & Related papers (2023-01-09T14:41:07Z) - Resource-frugal Hamiltonian eigenstate preparation via repeated quantum
phase estimation measurements [0.0]
Preparation of Hamiltonian eigenstates is essential for many applications in quantum computing.
We adopt ideas from variants of this method to implement a resource-frugal iterative scheme.
We characterise an extension involving a modification of the target Hamiltonian to increase overall efficiency.
arXiv Detail & Related papers (2022-12-01T20:07:36Z) - End-to-end resource analysis for quantum interior point methods and portfolio optimization [63.4863637315163]
We provide a complete quantum circuit-level description of the algorithm from problem input to problem output.
We report the number of logical qubits and the quantity/depth of non-Clifford T-gates needed to run the algorithm.
arXiv Detail & Related papers (2022-11-22T18:54:48Z) - Quantum key distribution rates from semidefinite programming [0.0]
We introduce an efficient algorithm for computing the key rate in quantum key distribution protocols.
The resulting algorithm is easy to implement and easy to use.
We use it to reanalyse experimental data to demonstrate how higher key rates can be achieved.
arXiv Detail & Related papers (2022-11-10T17:47:37Z) - Tight Cram\'{e}r-Rao type bounds for multiparameter quantum metrology
through conic programming [61.98670278625053]
It is paramount to have practical measurement strategies that can estimate incompatible parameters with best precisions possible.
Here, we give a concrete way to find uncorrelated measurement strategies with optimal precisions.
We show numerically that there is a strict gap between the previous efficiently computable bounds and the ultimate precision bound.
arXiv Detail & Related papers (2022-09-12T13:06:48Z) - Gradient-descent quantum process tomography by learning Kraus operators [63.69764116066747]
We perform quantum process tomography (QPT) for both discrete- and continuous-variable quantum systems.
We use a constrained gradient-descent (GD) approach on the so-called Stiefel manifold during optimization to obtain the Kraus operators.
The GD-QPT matches the performance of both compressed-sensing (CS) and projected least-squares (PLS) QPT in benchmarks with two-qubit random processes.
arXiv Detail & Related papers (2022-08-01T12:48:48Z) - Improved Quantum Algorithms for Fidelity Estimation [77.34726150561087]
We develop new and efficient quantum algorithms for fidelity estimation with provable performance guarantees.
Our algorithms use advanced quantum linear algebra techniques, such as the quantum singular value transformation.
We prove that fidelity estimation to any non-trivial constant additive accuracy is hard in general.
arXiv Detail & Related papers (2022-03-30T02:02:16Z) - Device-independent lower bounds on the conditional von Neumann entropy [10.2138250640885]
We introduce a numerical method to compute lower bounds on rates of quantum protocols.
We find substantial improvements over all previous numerical techniques.
Our method is compatible with the entropy accumulation theorem.
arXiv Detail & Related papers (2021-06-25T15:24:12Z) - Computing conditional entropies for quantum correlations [10.549307055348596]
In particular, we find new upper bounds on the minimal global detection efficiency required to perform device-independent quantum key distribution.
We introduce the family of iterated mean quantum R'enyi divergences with parameters $alpha_k = 1+frac12k-1$ for positive integers $k$.
We show that the corresponding conditional entropies admit a particularly nice form which, in the context of device-independent optimization, can be relaxed to a semidefinite programming problem.
arXiv Detail & Related papers (2020-07-24T15:27:51Z)
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.