Riemannian Optimization for Holevo Capacity
- URL: http://arxiv.org/abs/2501.11576v1
- Date: Mon, 20 Jan 2025 16:26:21 GMT
- Title: Riemannian Optimization for Holevo Capacity
- Authors: Chengkai Zhu, Renfeng Peng, Bin Gao, Xin Wang,
- Abstract summary: We formulate the computation of the Holevo capacity as an optimization problem on a product manifold constructed from probability distributions.<n>A gradient gradient descent algorithm is proposed to solve the problem, providing lower bounds on the classical capacity of general quantum channels.
- Score: 5.746235925946808
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Computing the classical capacity of a noisy quantum channel is crucial for understanding the limits of communication over quantum channels. However, its evaluation remains challenging due to the difficulty of computing the Holevo capacity and the even greater difficulty of regularization. In this work, we formulate the computation of the Holevo capacity as an optimization problem on a product manifold constructed from probability distributions and their corresponding pure input states for a quantum channel. A Riemannian gradient descent algorithm is proposed to solve the problem, providing lower bounds on the classical capacity of general quantum channels and outperforming existing methods in numerical experiments in both efficiency and scale.
Related papers
- Quantum-Channel Matrix Optimization for Holevo Bound Enhancement [87.57725685513088]
We propose a unified projected gradient ascent algorithm to optimize the quantum channel given a fixed input ensemble.<n> Simulation results demonstrate that the proposed quantum channel optimization yields higher Holevo bounds than input ensemble optimization.
arXiv Detail & Related papers (2026-02-19T04:15:03Z) - On small perturbations of coherent information [7.078713722203906]
Quantum capacity quantifies the amount of quantum information that can be transmitted by a quantum channel with an arbitrary small probability of error.<n>We develop perturbative methods for analyzing the behavior of coherent information of a quantum channel with respect to small perturbations of the input state.<n>We show how our criteria yield sufficient conditions for superadditivity of one-shot quantum capacity, and also for detecting a positive gap between one-shot private capacity and one-shot quantum capacity.
arXiv Detail & Related papers (2025-07-22T18:02:27Z) - On the Limits of Distributed Quantum Computing [0.9790236766474201]
Quantum algorithms can solve certain problems exponentially faster than classical ones.
In bandwidth-limited networks, quantum distributed networks have shown computational advantages over classical counterparts.
We focus on the LOCAL model of computation, a distributed computational model where computational power and communication bandwidth are unconstrained.
arXiv Detail & Related papers (2025-03-14T13:36:51Z) - Power Characterization of Noisy Quantum Kernels [52.47151453259434]
We show that noise may make quantum kernel methods to only have poor prediction capability, even when the generalization error is small.
We provide a crucial warning to employ noisy quantum kernel methods for quantum computation.
arXiv Detail & Related papers (2024-01-31T01:02:16Z) - Near-Term Distributed Quantum Computation using Mean-Field Corrections
and Auxiliary Qubits [77.04894470683776]
We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production.
We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
arXiv Detail & Related papers (2023-09-11T18:00:00Z) - Quantum Worst-Case to Average-Case Reductions for All Linear Problems [66.65497337069792]
We study the problem of designing worst-case to average-case reductions for quantum algorithms.
We provide an explicit and efficient transformation of quantum algorithms that are only correct on a small fraction of their inputs into ones that are correct on all inputs.
arXiv Detail & Related papers (2022-12-06T22:01:49Z) - Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the
Race to Practical Quantum Advantage [43.3054117987806]
We introduce a scalable procedure for harnessing classical computing resources to provide pre-optimized initializations for quantum circuits.
We show this method significantly improves the trainability and performance of PQCs on a variety of problems.
By demonstrating a means of boosting limited quantum resources using classical computers, our approach illustrates the promise of this synergy between quantum and quantum-inspired models in quantum computing.
arXiv Detail & Related papers (2022-08-29T15:24:03Z) - Fundamental limitations on optimization in variational quantum
algorithms [7.165356904023871]
A leading paradigm to establish such near-term quantum applications is variational quantum algorithms (VQAs)
We prove that for a broad class of such random circuits, the variation range of the cost function vanishes exponentially in the number of qubits with a high probability.
This result can unify the restrictions on gradient-based and gradient-free optimizations in a natural manner and reveal extra harsh constraints on the training landscapes of VQAs.
arXiv Detail & Related papers (2022-05-10T17:14:57Z) - Limitations of variational quantum algorithms: a quantum optimal
transport approach [11.202435939275675]
We obtain extremely tight bounds for standard NISQ proposals in both the noisy and noiseless regimes.
The bounds limit the performance of both circuit model algorithms, such as QAOA, and also continuous-time algorithms, such as quantum annealing.
arXiv Detail & Related papers (2022-04-07T13:58:44Z) - 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) - Circuit Symmetry Verification Mitigates Quantum-Domain Impairments [69.33243249411113]
We propose circuit-oriented symmetry verification that are capable of verifying the commutativity of quantum circuits without the knowledge of the quantum state.
In particular, we propose the Fourier-temporal stabilizer (STS) technique, which generalizes the conventional quantum-domain formalism to circuit-oriented stabilizers.
arXiv Detail & Related papers (2021-12-27T21:15:35Z) - Efficient Classical Computation of Quantum Mean Values for Shallow QAOA
Circuits [15.279642278652654]
We present a novel graph decomposition based classical algorithm that scales linearly with the number of qubits for the shallow QAOA circuits.
Our results are not only important for the exploration of quantum advantages with QAOA, but also useful for the benchmarking of NISQ processors.
arXiv Detail & Related papers (2021-12-21T12:41:31Z) - Quantum amplitude damping for solving homogeneous linear differential
equations: A noninterferometric algorithm [0.0]
This work proposes a novel approach by using the Quantum Amplitude Damping operation as a resource, in order to construct an efficient quantum algorithm for solving homogeneous LDEs.
We show that such an open quantum system-inspired circuitry allows for constructing the real exponential terms in the solution in a non-interferometric.
arXiv Detail & Related papers (2021-11-10T11:25:32Z) - Quantum computing critical exponents [0.0]
We show that the Variational Quantum-Classical Simulation algorithm admits a finite circuit depth scaling collapse when targeting the critical point of the transverse field Ising chain.
The order parameter only collapses on one side of the transition due to a slowdown of the quantum algorithm when crossing the phase transition.
arXiv Detail & Related papers (2021-04-02T17:38:20Z) - Boundaries of quantum supremacy via random circuit sampling [69.16452769334367]
Google's recent quantum supremacy experiment heralded a transition point where quantum computing performed a computational task, random circuit sampling.
We examine the constraints of the observed quantum runtime advantage in a larger number of qubits and gates.
arXiv Detail & Related papers (2020-05-05T20:11:53Z)
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.