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Lecture notes in computer science

Performance of Circuit-Based Blind Quantum Computation in NISQ Era

Mohit Joshi, Manoj Kumar Mishra, S. Karthikeyan

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1007/978-3-032-26349-0_13

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In the noisy intermediate-scale quantum (NISQ) era, quantum computing resources are increasingly provided through cloud platforms, enabling users to perform quantum computations without owning expensive hardware. However, delegating computations to remote servers raises a key challenge: ensuring the privacy of the client’s input, algorithm, and output. To address this issue, we propose a circuit-model blind quantum computation (CMBQC) protocol that conceals the target quantum computation while decoupling the encryption and decryption keys. This key-decoupled structure avoids gate-by-gate propagation of decryption information on the client side. We establish blindness of the target operation within its Pauli equivalence class and prove the verifiability of the protocol, where verification is achieved by estimating expectation values of randomly chosen Pauli observables, thereby substantially reducing the verification overhead. We further demonstrate a single-qubit implementation of the CMBQC protocol on an International Business Machines Corporation (IBM) superconducting quantum system. The simple structure and low verification cost of the CMBQC protocol make it a promising framework for secure delegated quantum computation, with potential applications in quantum cloud computing.
Blind Quantum Computation lets a limited-capability client delegate its complex computation to a remote server without revealing its data or computation. Several such protocols have been proposed under varied quantum computing models. However, these protocols either rely on highly entangled resource states (in measurement-based models) or are based on non-parametric resource sets (in circuit-based models). These restrictions hinder the practical applicability of such an algorithm in the NISQ era, especially concerning the hybrid quantum-classical infrastructure, which depends on parametric gates. We present a protocol for universal blind quantum computation based on recursive decryption of parametric rotation gates, which does not require a highly entangled state at the server side and substantially reduces the communication rounds required for practical prototyping of secure variational algorithms.
In the NISQ era, there is a need for resource-efficient proof-of-principle experiments that can be built up to genuine utility. Single-qubit classifiers (SQCs) are small-scale hybrid quantum-classical machines capable of performing a basic machine learning task: classifying data. In principle, these can be scaled up to many-qubit quantum classifiers capable of quantum computational advantage. Another type of quantum advantage is enabled by blind quantum computation (BQC), wherein a client may run delegated quantum computations on an untrusted server with information-theoretic security. In this paper, we develop a framework and propose a prototype experiment for a SQC where it is known to the server that a classification is being performed, but the data and outcome stay hidden, i.e., it performs partially-blind SQC (PB-SQC). This can be integrated into a quantum network to deliver quantum-secured classifications to remote clients; we study this for a heterogeneous quantum network link in which entanglement is shared between a server and a client equipped with a multiplexed solid-state quantum memory using entanglement swapping. The framework we develop for PB-SQC on this setup is tested in a simulation with realistic hardware parameters on a real-world credit card transaction fraud database with classification outcomes approaching those of its equivalent classical deep-belief network. In addition, we show how a two-qubit classifier (TQC) instead of a SQC enables verification of the computation. These results pave the way towards a short- to mid-term quantum network offering use-case-ready quantum applications.