Quantum communication complexity beyond Bell nonlocality
- URL: http://arxiv.org/abs/2106.06552v1
- Date: Fri, 11 Jun 2021 18:00:09 GMT
- Title: Quantum communication complexity beyond Bell nonlocality
- Authors: Joseph Ho, George Moreno, Samura\'i Brito, Francesco Graffitti,
Christopher L. Morrison, Ranieri Nery, Alexander Pickston, Massimiliano
Proietti, Rafael Rabelo, Alessandro Fedrizzi, and Rafael Chaves
- Abstract summary: Efficient distributed computing offers a scalable strategy for solving resource-demanding tasks.
Quantum resources are well-suited to this task, offering clear strategies that can outperform classical counterparts.
We prove that a new class of communication complexity tasks can be associated to Bell-like inequalities.
- Score: 87.70068711362255
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Efficient distributed computing offers a scalable strategy for solving
resource-demanding tasks such as parallel computation and circuit optimisation.
Crucially, the communication overhead introduced by the allotment process
should be minimised -- a key motivation behind the communication complexity
problem (CCP). Quantum resources are well-suited to this task, offering clear
strategies that can outperform classical counterparts. Furthermore, the
connection between quantum CCPs and nonlocality provides an
information-theoretic insights into fundamental quantum mechanics. Here we
connect quantum CCPs with a generalised nonlocality framework -- beyond the
paradigmatic Bell's theorem -- by incorporating the underlying causal
structure, which governs the distributed task, into a so-called nonlocal hidden
variable model. We prove that a new class of communication complexity tasks can
be associated to Bell-like inequalities, whose violation is both necessary and
sufficient for a quantum gain. We experimentally implement a multipartite CCP
akin to the guess-your-neighbour-input scenario, and demonstrate a quantum
advantage when multipartite Greenberger-Horne-Zeilinger (GHZ) states are shared
among three users.
Related papers
- Projective Quantum Eigensolver with Generalized Operators [0.0]
We develop a methodology for determining the generalized operators in terms of a closed form residual equations in the PQE framework.
With the application on several molecular systems, we have demonstrated our ansatz achieves similar accuracy to the (disentangled) UCC with singles, doubles and triples.
arXiv Detail & Related papers (2024-10-21T15:40:22Z) - Scalable & Noise-Robust Communication Advantage of Multipartite Quantum Entanglement [0.0]
Quantum resources offer advantages over classical methods in addressing this challenge.
We show that when the receiver and the senders share a multi-qubit Greenberger-Horne-Zeilinger (GHZ) state, certain global functions of the distributed inputs can be computed with only one bit of classical communication from each sender.
We also show that the entanglement-based protocol exhibits significant robustness under white noise.
arXiv Detail & Related papers (2024-09-20T05:17:09Z) - Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Attention-Based Deep Reinforcement Learning for Qubit Allocation in Modular Quantum Architectures [1.8781124875646162]
This research contributes to the advancement of scalable quantum computing systems by introducing a novel learning-based approach for efficient quantum circuit compilation and mapping.
In this work, we propose a novel approach employing Deep Reinforcement Learning (DRL) methods to learn theses for a specific multi-core architecture.
arXiv Detail & Related papers (2024-06-17T12:09:11Z) - eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels [98.314893665023]
Quantum computing has sparked a potential synergy between quantum entanglement and cooperation in multi-agent environments.
Current state-of-the-art quantum MARL (QMARL) implementations rely on classical information sharing.
eQMARL is a distributed actor-critic framework that facilitates cooperation over a quantum channel.
arXiv Detail & Related papers (2024-05-24T18:43:05Z) - Separable Power of Classical and Quantum Learning Protocols Through the Lens of No-Free-Lunch Theorem [70.42372213666553]
The No-Free-Lunch (NFL) theorem quantifies problem- and data-independent generalization errors regardless of the optimization process.
We categorize a diverse array of quantum learning algorithms into three learning protocols designed for learning quantum dynamics under a specified observable.
Our derived NFL theorems demonstrate quadratic reductions in sample complexity across CLC-LPs, ReQu-LPs, and Qu-LPs.
We attribute this performance discrepancy to the unique capacity of quantum-related learning protocols to indirectly utilize information concerning the global phases of non-orthogonal quantum states.
arXiv Detail & Related papers (2024-05-12T09:05:13Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - Enhancing Quantum Annealing via entanglement distribution [1.1470070927586018]
Quantum Annealing has proven to be a powerful tool to tackle several optimization problems.
Its performance is severely impacted by the limited connectivity of the underlying quantum hardware.
We present a novel approach to address these issues, by describing a method to implement non-local couplings.
arXiv Detail & Related papers (2022-12-05T18:18:58Z) - Entanglement and Causal Relation in distributed quantum computation [0.0]
We investigate two different aspects of entanglement and classical communication in distributed quantum computation (DQC)
In the first part, we analyze implementable computation over a given quantum network resource by introducing a new concept, quantum network coding for quantum computation.
In the second part, we show that entanglement required for local state discrimination can be substituted by less entanglement by increasing the rounds of classical communication.
arXiv Detail & Related papers (2022-02-14T07:23:17Z) - Realization of arbitrary doubly-controlled quantum phase gates [62.997667081978825]
We introduce a high-fidelity gate set inspired by a proposal for near-term quantum advantage in optimization problems.
By orchestrating coherent, multi-level control over three transmon qutrits, we synthesize a family of deterministic, continuous-angle quantum phase gates acting in the natural three-qubit computational basis.
arXiv Detail & Related papers (2021-08-03T17:49:09Z)
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.