Direct Minimum-Knowledge Computations (Extended Abstract)

Russell Impagliazzo, Moti M. Yung

Mordechai M. Yung

Christian Cachin, Jan L. Camenisch

Abstract. We present an efficient and fair protocol for secure two-party computation in the optimistic model, where a partially trusted third party T is available, but not involved in normal protocol executions. T is needed only if communication is disrupted or if one of the two parties misbehaves. The protocol guarantees that although one party may terminate the protocol at any time, the computation remains fair for the other party. Communication is over an asynchronous network. All our protocols are based on efficient proofs of knowledge and involve no general zero-knowledge tools. As intermediate steps we describe efficient verifiable oblivious transfer and verifiable secure function evaluation protocols, whose security is proved under the decisional Diffie-Hellman assumption. 1

Masanori Ohya, Igor Vasil'evich Volovich

Esther Villar-Rodríguez, Eneko Osaba, Izaskun Oregi +2 more

ABSTRACT Quantum computing is poised to transform computational paradigms across science and industry. As the field evolves, it can benefit from established classical methodologies, including promising paradigms such as Transfer of Knowledge (ToK). This work serves as a brief, self‐contained reference for ToK, unifying its core principles under a single formal framework. We introduce a joint notation that consolidates and extends prior work in Transfer Learning and Transfer Optimisation, bridging traditionally separate research lines and enabling a common language for knowledge reuse. Building on this foundation, we classify existing ToK strategies and principles into a structured taxonomy that helps researchers position their methods within a broader conceptual map. We then extend key transfer protocols to quantum computing, introducing two novel use cases—reverse annealing and multitasking Quantum Approximate Optimization Algorithm (QAOA)—alongside a sequential Variational Quantum Eigensolver (VQE) approach that supports and validates prior findings. These examples highlight ToK's potential to improve performance and generalisation in quantum algorithms. Finally, we outline challenges and opportunities for integrating ToK into quantum computing, emphasising its role in reducing resource demands and accelerating problem‐solving. This work lays the groundwork for future synergies between classical and quantum computing through a shared, transferable knowledge framework.

Sangbin Lee, Qi Jian Lim, Charles Ross +5 more

It is well known that electromagnetic computations are computationally demanding. Interestingly, many such problems can be recast to be solved by quantum annealing. Quantum annealing, a kind of quantum computer, utilizes quantum tunneling for state transitions, which enables one to find the global minimum in a complex energy landscape. Part I of this article explains quantum annealing for the classical electromagnetic community, assuming little knowledge of quantum theory. It reviews the basic principle and recent advances in quantum annealing to extend its applications, such as a hybrid quantum-classical annealing algorithm. Part II presents various examples of electromagnetic problems that can be solved by quantum annealing. These are 1) optimization of a reconfigurable directional metasurface, 2) finding current distribution in an arbitrary wire antenna, 3) finding charge and field distributions in a static condition, and 4) optimization of source excitation to focus fields in hyperthermia. Lastly, the performance of the quantum annealer is compared with classical solvers to deduce the type of applications in which a quantum annealer of current technologies can be preferred in practice.