Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Quantum Reports

Theory and Applications of Quantum Hashing

Farid Mansurovich Ablayev, Kamil Ravilevich Khadiev, Alexander Vasiliev, Mansur Ziiatdinov

Published May 15, 2025• 8 citations
Publisher

Abstract

We review recent results on quantum one-way functions, including quantum fingerprinting or quantum hashing (we use these two terms as synonyms even though they have very small difference). This includes the analysis of their properties, different modifications, circuit implementation on an IBM Q platform, as well as on an experimental quantum setup. We discuss computational aspects of quantum hashing, its cryptographic properties and possible usage in communication protocols and algorithms.

DOI
10.3390/quantum7020024

Related papers

On Quantum Fingerprinting and Quantum Cryptographic Hashing

Farid Mansurovich Ablayev, Marat Ablayev

Fingerprinting and cryptographic hashing have quite different usages in computer science, but have similar properties. Interpretation of their properties is determined by the area of their usage: fingerprinting methods are methods for constructing efficient randomized and quantum algorithms for computational problems, whereas hashing methods are one of the central cryptographical primitives. Fingerprinting and hashing methods are being developed from the mid of the previous century, whereas quantum fingerprinting and quantum hashing have a short history. In this chapter, we investigate quantum fingerprinting and quantum hashing. We present computational aspects of quantum fingerprinting and quantum hashing and discuss cryptographical properties of quantum hashing.

InTech eBooks•May 30, 2018•0 citations

Quantum Fingerprinting and Quantum Hashing. Computational and Cryptographical Aspects

Farid Mansurovich Ablayev, Marat Ablayev, Alexander Vasiliev +1 more

Rusins Freivalds was one of the first researchers who introduced methods (later called fingerprinting) for constructing efficient classical randomized and quantum algorithms.Fingerprinting and cryptographic hashing have quite different usages in computer science, but have similar properties.Interpretation of their properties is determined by the area of their usage: fingerprinting methods are methods for constructing efficient randomized and quantum algorithms for computational problems, while hashing methods are one of the central cryptographical primitives.Fingerprinting and hashing methods are being developed from the mid of the previous century, while quantum fingerprinting and quantum hashing have a short history.In the paper we present computational aspects of quantum fingerprinting, discuss cryptographical properties of quantum hashing, and present the possible use of quantum hashing for quantum hash-based message authentication codes.

Baltic Journal of Modern Computing•Dec 19, 2016•24 citations

Binary quantum hashing

Alexander Vasiliev

We propose a binary quantum hashing technique that allows to present binary inputs by quantum states. We prove the cryptographic properties of the quantum hashing, including its collision resistance and preimage resistance. We also give an efficient quantum algorithm that performs quantum hashing, and altogether this means that this function is quantum one-way. The proposed construction is asymptotically optimal in the number of qubits used.

Russian Mathematics•Jul 21, 2016•5 citations

Quantum hashing algorithm implementation

Aliya Khadieva

We implement a quantum hashing algorithm which is based on a fingerprinting technique presented by Ambainis and Frievalds, 1988, on gate-based quantum computers. This algorithm is based on a quantum finite automaton for a unary language $\mathtt{MOD_p}$, where $ \mathtt{MOD_p} = \{ a^{i \cdot p} \mid i \geq 0 \} $, for any prime number $p$. We consider 16-qubit and 27-qubit IBMQ computers with the special graphs of qubits representing nearest neighbor architecture that is not Linear Nearest Neighbor (LNN) one. We optimize quantum circuits for the quantum hashing algorithm with respect to minimizing the number of control operators as the most expensive ones. We apply the same approach for an optimized circuit implementation of Quantum Fourier Transform (QFT) operation on the aforementioned machines because QFT and hashing circuits have common parts.

arXiv:2407.10136•Jul 14, 2024•2 citations

On the concept of cryptographic quantum hashing

Farid Mansurovich Ablayev, Marat Ablayev

In the letter we define the notion of a quantum resistant ( -resistant) hash function which consists of a combination of pre-image (one-way) resistance ( ε -resistance) and collision resistance ( δ -resistance) properties. We present examples and discussion that supports the idea of quantum hashing. We present an explicit quantum hash function which is ‘balanced’, one-way resistant and collision resistant and demonstrate how to build a large family of quantum hash functions. Balanced quantum hash functions need a high degree of entanglement between the qubits. We use a phase transformation technique to express quantum hashing constructions, which is an effective way of mapping hash states to coherent states in a superposition of time-bin modes. The phase transformation technique is ready to be implemented with current optical technology.

arXiv:1509.01268•Laser Physics Letters•Nov 10, 2015•28 citations

Quantum Hashing Circuit Optimization for Arbitrary Qubit Connectivity Graphs Based on 1-Covering Path

Kamil Khadiev, Aliya Khadieva, Vadim Sagitov +2 more

One of the obstacles to the widespread adoption of quantum computing is the problem of efficient circuit synthesis. Current quantum hardware has limited connections between qubits, with each qubit connected to only a few others. This means that the circuit has to be transformed to accommodate this. In this paper, we present an algorithm that converts a circuit containing a sequence of CNOT gates into a form that is suitable for arbitrary quantum computer architectures. Although we demonstrate the algorithm only in the context of quantum fingerprinting, similar gate sequences are prevalent in quantum algorithms; for instance, they are present in the textbook quantum Fourier transform. We present a quantum circuit implementation of the quantum hashing algorithm (quantum fingerprinting algorithm) for a quantum device with restrictions on the application of two-qubit gates that are expressed as a qubit connectivity graph. As an example of usage of the technique, we apply it to quantum finite automata recognizing the unary $MOD_p=\{a^\ell: \ell \bmod p=0\}$ language, and the $EQ_p=\{a^\ell b^r: \ell \equiv r \pmod p\}$ language. Given the enhancements that our algorithm provides~-- for instance, in one case it achieves a 16\%--17\% decrease in CNOT circuit cost~-- we believe it could also be useful in a broader quantum compilation context.

quant-pharXiv:2608.09134•Aug 11, 2026•0 citations
We review recent results on quantum one-way functions, including quantum fingerprinting or quantum hashing (we use these two terms as synonyms even though they have very small difference). This includes the analysis of their properties, different modifications, circuit implementation on an IBM Q platform, as well as on an experimental quantum setup. We discuss computational aspects of quantum hashing, its cryptographic properties and possible usage in communication protocols and algorithms.
Fingerprinting and cryptographic hashing have quite different usages in computer science, but have similar properties. Interpretation of their properties is determined by the area of their usage: fingerprinting methods are methods for constructing efficient randomized and quantum algorithms for computational problems, whereas hashing methods are one of the central cryptographical primitives. Fingerprinting and hashing methods are being developed from the mid of the previous century, whereas quantum fingerprinting and quantum hashing have a short history. In this chapter, we investigate quantum fingerprinting and quantum hashing. We present computational aspects of quantum fingerprinting and quantum hashing and discuss cryptographical properties of quantum hashing.
Rusins Freivalds was one of the first researchers who introduced methods (later called fingerprinting) for constructing efficient classical randomized and quantum algorithms.Fingerprinting and cryptographic hashing have quite different usages in computer science, but have similar properties.Interpretation of their properties is determined by the area of their usage: fingerprinting methods are methods for constructing efficient randomized and quantum algorithms for computational problems, while hashing methods are one of the central cryptographical primitives.Fingerprinting and hashing methods are being developed from the mid of the previous century, while quantum fingerprinting and quantum hashing have a short history.In the paper we present computational aspects of quantum fingerprinting, discuss cryptographical properties of quantum hashing, and present the possible use of quantum hashing for quantum hash-based message authentication codes.
We implement a quantum hashing algorithm which is based on a fingerprinting technique presented by Ambainis and Frievalds, 1988, on gate-based quantum computers. This algorithm is based on a quantum finite automaton for a unary language MODp\mathtt{MOD_p}MODp​, where $ \mathtt{MOD_p} = \{ a^{i \cdot p} \mid i \geq 0 \} $, for any prime number ppp. We consider 16-qubit and 27-qubit IBMQ computers with the special graphs of qubits representing nearest neighbor architecture that is not Linear Nearest Neighbor (LNN) one. We optimize quantum circuits for the quantum hashing algorithm with respect to minimizing the number of control operators as the most expensive ones. We apply the same approach for an optimized circuit implementation of Quantum Fourier Transform (QFT) operation on the aforementioned machines because QFT and hashing circuits have common parts.
In the letter we define the notion of a quantum resistant ( -resistant) hash function which consists of a combination of pre-image (one-way) resistance ( ε -resistance) and collision resistance ( δ -resistance) properties. We present examples and discussion that supports the idea of quantum hashing. We present an explicit quantum hash function which is ‘balanced’, one-way resistant and collision resistant and demonstrate how to build a large family of quantum hash functions. Balanced quantum hash functions need a high degree of entanglement between the qubits. We use a phase transformation technique to express quantum hashing constructions, which is an effective way of mapping hash states to coherent states in a superposition of time-bin modes. The phase transformation technique is ready to be implemented with current optical technology.
One of the obstacles to the widespread adoption of quantum computing is the problem of efficient circuit synthesis. Current quantum hardware has limited connections between qubits, with each qubit connected to only a few others. This means that the circuit has to be transformed to accommodate this. In this paper, we present an algorithm that converts a circuit containing a sequence of CNOT gates into a form that is suitable for arbitrary quantum computer architectures. Although we demonstrate the algorithm only in the context of quantum fingerprinting, similar gate sequences are prevalent in quantum algorithms; for instance, they are present in the textbook quantum Fourier transform. We present a quantum circuit implementation of the quantum hashing algorithm (quantum fingerprinting algorithm) for a quantum device with restrictions on the application of two-qubit gates that are expressed as a qubit connectivity graph. As an example of usage of the technique, we apply it to quantum finite automata recognizing the unary MODp={aℓ:ℓ mod p=0}MOD_p=\{a^\ell: \ell \bmod p=0\}MODp​={aℓ:ℓmodp=0} language, and the EQp={aℓbr:ℓ≡r(modp)}EQ_p=\{a^\ell b^r: \ell \equiv r \pmod p\}EQp​={aℓbr:ℓ≡r(modp)} language. Given the enhancements that our algorithm provides~-- for instance, in one case it achieves a 16\%--17\% decrease in CNOT circuit cost~-- we believe it could also be useful in a broader quantum compilation context.