A5009862855- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Complexity and Algorithms in Graphs
- Machine Learning and Algorithms
- semigroups and automata theory
- Computability, Logic, AI Algorithms
- Algorithms and Data Compression
- Quantum Mechanics and Applications
- Chaos-based Image/Signal Encryption
- Formal Methods in Verification
- Quantum-Dot Cellular Automata
- Optimization and Search Problems
- DNA and Biological Computing
- Cryptography and Data Security
- Cellular Automata and Applications
- Cryptographic Implementations and Security
- Coding theory and cryptography
- Advanced Data Storage Technologies
- Cloud Computing and Resource Management
- Advanced Graph Theory Research
- Advanced Fiber Laser Technologies
- Orbital Angular Momentum in Optics
- Optical Network Technologies
- Distributed systems and fault tolerance
- Stochastic processes and statistical mechanics
Kazan Federal University
2015-2024
Kazan Scientific Center
2020-2022
Russian Academy of Sciences
2020
Kazan E. K. Zavoisky Physical-Technical Institute
2020
Tatarstan Academy of Sciences
2011-2013
Max Planck Society
2005
University of Bonn
1995-2003
Max Planck Institute for Mathematics
2003
This is a review of quantum methods for machine learning problems that consists two parts. The first part, "quantum tools", presents the fundamentals qubits, registers, and states, introduces important tools based on known search algorithms SWAP-test, discusses basic procedures used methods. second classification algorithms", several can be accelerated by using subroutines classification.
We present a version of quantum hash functions based on non-binary discrete functions. The proposed procedure is 'classical-quantum', that is, it takes classical bit string as an input and produces state. resulting function has the property one-way (pre-image resistance); in addition properties analogous to cryptographic second pre-image resistance collision resistance.
In the paper we define a notion of resistant quantum hash function which combines pre-image (one-way) resistance and collision resistance. setting one-way property are correlated: "more" is "less" it vice versa. We present an explicit "balanced" demonstrate how to build large family balanced functions.
This is a review of quantum methods for machine learning problems that consists two parts. The first part, "quantum tools", presented some the fundamentals and introduced several tools based on known search algorithms. second part presents classification in can be accelerated with subroutines. We have chosen supervised tasks as typical to illustrate use classification.
In the letter we define notion of a quantum resistant (-resistant) hash function which consists combination pre-image (one-way) resistance (ε-resistance) and collision (δ-resistance) properties.
Rusins Freivalds was one of the first researchers who introduced methods (later called fingerprinting) for constructing efficient classical randomized and quantum algorithms.Fingerprinting cryptographic hashing have quite different usages in computer science, but similar properties.Interpretation their properties is determined by area usage: fingerprinting are algorithms computational problems, while central cryptographical primitives.Fingerprinting being developed from mid previous century,...
In the paper we develop a method for constructing quantum algorithms computing Boolean functions by ordered read-once branching programs (quantum OBDDs). Our is based on fingerprinting technique and representation of their characteristic polynomials. We use circuit notation desired presentation. For several known our approach provides optimal QOBDDs. Namely consider such as Equality, Palindrome, Permutation Matrix Test. also propose generalization apply it to variant Hidden Subgroup Problem.
In this paper, we develop the fingerprinting technique of calculation Boolean functions in quantum models. The use is demonstrated on example function MOD m class OBDD (oblivious read-once branching programs). Next, potentialities are realisation 'equality' model communication with a referee (the SMP model) and examples recognition languages automata. All given realisations various models (OBDD, model, finite automaton) asymptotically optimal. authors thank Juhani Karhumäki for invitation to...