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Russian Cloud Platform
for Quantum Computing

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The Leading Research Center for Quantum Computing was created on the basis of the Russian Quantum Center to develop an experimental prototype of a quantum computing device and a cloud platform for its remote operation.

The project is carried out jointly with leading scientific organizations: Lebedev Physical Institute of the Russian Academy of Sciences, Skolkovo Institute of Science and Technology, and Valiev Institute of Physics and Technology of the Russian Academy of Sciences.

This consortium will develop a five-qubit ion-based quantum computer and a stack of quantum software and mathematical models that allow applying new approaches to the implementation of quantum algorithms. A unique feature of the project is the use of qudits – multi-level computational units of quantum information.

The LRC project is supported by the Russian Venture Company and the Ministry of Digital Development, Communications and Mass Media of the Russian Federation. The industrial partner of the project is SP Kvant LLC.

Quantum Platform

Quantum computers use the effects of quantum superposition and entanglement for solving computational tasks. Technologies based on quantum computing can substantially outperform classical computers in numerous areas, such as cryptanalysis, complex systems modeling, optimization, machine learning, and artificial intelligence.

One of the critical issues in developing quantum computing devices is the selection of an underlying physical system that enables the implementation of qubits – basic information units of quantum computers, similar to classical bits.

In the LRC project, the experimental prototype of a quantum computing device is implemented based on trapped ions. This physical system is considered one of the most promising according to the research results by the global scientific community and commercial organizations in the field of quantum computing.

The development of the experimental prototype of a quantum computing device and cloud platform is carried out according to the Russian Quantum Technologies Roadmap and is directly related to the implementation of a key subtechnology in quantum computing – the development of an ion-trap quantum computing device.

Ion platform

Quantum computer with 2-5 qubits, implemented on Ytterbium ions in linear Paul trap. Fidelity of single-qubit operations – 0,9, fidelity of two-qubit operations – 0,8

Qudits

Quantum computer allows utilizing qudits and performing qudit operations, which contributes to better scalability and reduction of operations count required for implementing quantum algorithms

Algorithms

Quantum computer is able to perform basic quantum algorithms, such as Bernstein–Vazirani and Grover

Quantum computing can be applied to solving a wide range of industrial tasks. The most popular and demanded areas include optimization, modeling of complex physical systems (for example, chemical compounds and materials), and machine learning.

Our solution is built upon a 3-layered modular structure, which allows us to implement a convenient high-level interface, translate the input algorithm into optimal intermediate representation and dispatch the task to an actual quantum computing unit.

Quantum Compitation Solution Scheme

Documents

Certificates

State Registration Certificate № 2021662881 for Computer Software dated 08/06/2021

Software for quantum state preparation

The purpose of the program is to construct a quantum circuit that encodes a circuit with any set of gates that are available on a quantum computer implemented on a trapped-ion system. Quantum state is encoded by a shallow equivalent circuit using a variational algorithm

State Registration Certificate № 2021663103 for Computer Software dated 08/11/2021

Software for searching families of states that can be prepared using a trapped ion-based processor

The software calculates the population of families of states generated by a particular quantum circuit, searches for states belonging to the target family of states, and determines whether a state belongs to a specific family of states

Patents

Patent № 2761771 dated 12/13/2021

Method for conducting quantum computations using qudits

The method will reduce the number of elementary operations required to implement quantum algorithms, thereby increasing the resulting fidelity

Life Cycle Processes

Software development life cycle

Functional capabilities

Functional capabilities

Manuals

User's Manual

Publications

  1. Kiktenko E.O., Kulikov D.A., Yashin V.I., Mastiukova A.S., Fedorov A.K. A model of a quantum processor based on a pseudostochastic representation// Nanoindustry. – 2023. – V. 16. – №S9-2 (119). – C. 445-448.
  1. N.V. Semenin, A.S. Borisenko, I.V. Zalivako, I.A. Semerikov, M.D. Aksenov, K.Yu. Khabarova, N.N. Kolachevsky, Determination of the heating rate and temperature of ion chains in a linear Paul trap from the dephasing of Rabi oscillations, JETP Letters 116, 74 (2022) [in Russian].
  2. M.S. Sapova and A.K. Fedorov, Variational quantum eigensolver techniques for simulating carbon monoxide oxidation, Commun. Phys. 5, 199 (2022);
  3. A.I. Lotkov, V. Gritsev, A.K. Fedorov, and D.V. Kurlov, Floquet integrability and long-range entanglement generation in the one-dimensional quantum Potts model, Physical Review B 105, 144306 (2022);
  4. D. Rabinovich, R. Sengupta, E. Campos, V. Akshay, and J. Biamonte, Progress towards analytically optimal angles in quantum approximate optimisation, Mathematics 10, 2601 (2022);
  5. M.A. Gavreev, A.S. Mastiukova, E.O. Kiktenko, and A.K. Fedorov, Learning entanglement breakdown as a phase transition by confusion, New J. Phys. 24, 073045 (2022);
  6. A.V. Antipov, E.O. Kiktenko, A.K. Fedorov Efficient realization of quantum primitives for Shor’s algorithm using PennyLane library// PLOS ONE. – 2022. – Т. 17. – № 7. – С. e0271462.
  7. Aksenov M. A. et al. Realizing quantum gates with optically addressable Yb+ 171 ion qudits //Physical Review A. – 2023. – Т. 107. – №. 5. – С. 052612.
  8. M.A. Gavreev, A.S. Mastiukova, E.O. Kiktenko, A.K. Fedorov. Learning entanglement breakdown as a phase transition by confusion// New Journal of Physics. – 2022. – Т. 24. – С. 073045.
  9. Akshay V. et al. On Circuit Depth Scaling For Quantum Approximate Optimization //Physial review A 106, 042438 – 2022
  10. Bantysh B.I., Bogdanov Y.I. Quantum tomography for quantum systems optimization // Proc. SPIE / ed. Rudenko K. V., Lukichev V.F. SPIE, 2022. Vol. 12157. P. 121571U
  1. E.O. Kiktenko, A.S. Nikolaeva, and A.K. Feodorov, Quantum computing using multilevel quantum systems, Nanoindustry 13, 649 (2020) [in Russian].
  2. K.Yu. Khabarova, I.V. Zalivako, I.A. Semerikova, N.V. Semenin, P.L. Sidorov, P.A. Vishnyakov, and N.N. Kolachevsky, Ion traps and features of thier application in universal quantum computing, Nanoindustry 13, 648 (2020) [in Russian].
  3. A. Uvarov, J. Biamonte, and D. Yudin, Variational quantum eigensolver for frustrated quantum systems, Phys. Rev. B 102, 075104 (2020).
  4. A. Berezutskii, M. Beketov, D. Yudin, Z. Zimborás, and J. Biamonte, Probing criticality in quantum spin chains with neural networks, J. Phys. Complex. 1, 03LT01 (2020).
  5. A. Kardashin, A. Uvarov, D. Yudin, and J. Biamonte, Certified variational quantum algorithms for eigenstate preparation, Phys. Rev. A 102, 052610 (2020).
  1. I.A. Luchnikov, E.O. Kiktenko, M.A. Gavreev, H. Ouerdane, S.N. Filippov, and A.K. Fedorov, Probing non-Markovian quantum dynamics with data-driven analysis: Beyond “black-box” machine learning models, Nanoindustry 14, 744 (2020) [in Russian].
  2. E.O. Kiktenko, V.I. Yashin, A.S. Mastiukova, and A.K. Fedorov Extracting non-Markovian component of quantum dynamics within the pseudo-stochastic representation, Nanoindustry 14, 747 (2020) [in Russian].
  3. A.S. Mastiukova, E.O. Kiktenko, V.I. Yashin, and A.K. Fedorov Analysing Markovian and non-Markovian quantum dynamics in pseudostochastic representation, Nanoindustry 14, 752 (2020) [in Russian].
  4. I.A. Luchnikov, A.V. Berezutskii, E.O. Kiktenko, and A.K. Fedorov, Efficient simulation of multiqubit circuits, Nanoindustry 14, 758 (2020) [in Russian].
  5. I.V. Zalivako, I.A. Semerikov, A.S. Borisenko, M.D. Aksenov, K.Yu. Khabarova, and N. N. Kolachevsky, Experimental study of the optical qubit on the 435-nm quadrupole transition in the 171Yb+ ion, JETP Lett. 114, 59 (2021).
  6. E.O. Kiktenko, D.O. Norkin, and A.K. Fedorov, Confidence polytopes for quantum process tomography, New J. Phys. 23, 123022 (2021); arXiv:2109.04734.
  7. I.V. Zalivako, I.A. Semerikov, A.S. Borisenko, M.D. Aksenov, K.Yu. Khabarova, and N. N. Kolachevsky, Experimental study of the optical qubit on the 435-nm quadrupole transition in the 171Yb+ ion, JETP Lett.  114, 59 (2021).
  8. B.I. Bantysh and Yu.I. Bogdanov, Quantum tomography of noisy ion-based qudit, Laser Phys. Lett. 18, 015203 (2021); arXv:2011.04179.
  9. A. Kardashin, A. Uvarov, and J. Biamonte, Quantum machine learning tensor network states, Front. Phys. 8, 586374 (2021); arXiv:1804.02398.
  10. J. Biamonte, Universal variational quantum computation, Phys. Rev. A. 103, L030401 (2021); arXiv:1903.04500.
  11. O.V. Borzenkova, G.I. Struchalin, A.S. Kardashin, V.V. Krasnikov, N.N. Skryabin, S.S. Straupe, S.P. Kulik, and J.D. Biamonte, Variational simulation of Schwinger’s Hamiltonian with polarisation qubits, Appl. Phys. Lett. 118, 144002 (2021); arXiv:2009.09551.
  12. H. Philathong, V.N. Akshay, K. Samburskaya, and J. Biamonte, Computational phase transitions: Benchmarking Ising machines and quantum optimisers, J. Phys. Complexity 2, 011002 (2021); arXiv:2009.05579.
  13. E. Campos, A. Nasrallah, and J. Biamonte, Abrupt transitions in variational quantum circuit training, Phys. Rev. A 103, 032607 (2021); arXiv:2010.09720.
  14. A. Uvarov and J. Biamonte, On barren plateaus and cost function locality in variational quantum algorithms, J. Phys. A: Math. Theor. 54, 245301 (2021); arXiv:2011.10530.
  15. V. Akshay, D. Rabinovich, E. Campos, and J. Biamonte, Parameter concentration in quantum approximate optimization, Phys. Rev. A 104, L010401 (2021); arXiv:2103.11976.
  16. A. Kardashin, A. Pervishko, J. Biamonte, and D. Yudin, Numerical hardware-efficient variational quantum simulation of a soliton solution, Phys. Rev. A 104, 020402 (2021); arXiv:2105.06208.
  17. V. Akshay, H. Philathong, I. Zacharov, and J. Biamonte, Reachability deficits in quantum approximate optimization of graph problems, Quantum 5, 532 (2021); arXiv:2007.09148.
  1. A.S. Nikolaeva, E.O. Kiktenko, and A.K. Fedorov, Efficient realization of quantum algorithms with qudits, arXiv:2111.04384.
  2. I.A. Luchnikov, A.V. Berezutskii, and A.K. Fedorov, Simulating quantum circuits using the multi-scale entanglement renormalization ansatz, arXiv:2112.14046.

Media

07/13/2023

Hi-tech exhibition in quantum technology

Future Technologies Forum

07/13/2023

The most productive quantum computer in Russia was presented to Putin

GAZETA.RU

07/13/2023

Exhibition of quantum technology innovations

Official Internet Resources of the President of Ru

07/13/2023

Putin assured the participants of the Future Technologies Forum that Russia will not give up under external pressure and will continue to move forward

ROSSIYSKAYA GAZETA

04/05/2023

A quantum computer was launched on a ordinary PC

GAZETA.RU

04/05/2023

Russian physicists connected to a quantum computer remotely

MIR 24

04/05/2023

A quantum computer with cloud access was launched from a ordinary PC

NAUKA.RF

04/05/2023

The first time researchers successfully connect to a quantum computer remotely

TASS

05/27/2022

Russian scientists patent qudit-based quantum processor (in Russian)

PC News

05/27/2022

Russian scientists patent new quantum processor architecture (in Russian)

RB.RU

05/27/2022

New quantum processor architecture patented in Russia (in Russian)

RuNews24

05/26/2022

New quantum processor architecture patented in Russia (in Russian)

3D News

05/26/2022

Russian scientists patent physical implementation of qudit-based quantum computer (in Russian)

Atomnaya energiya

05/26/2022

Scientists from Russia patent new quantum processor architecture (in Russian)

Cnews

05/26/2022

Russian scientists patent new quantum processor architecture (in Russian)

Connect

05/26/2022

Scientists from Russian Quantum Center patent qudit-based computer (in Russian)

Ekonomika Segodnya

05/26/2022

Russian scientists patent new quantum processor architecture (in Russian)

Habr

05/26/2022

New qudit-based quantum computer architecture patented in Russia (in Russian)

ICT Moscow

05/26/2022

Russian scientists patent qudit-based quantum processor (in Russian)

IXBT

05/26/2022

Russian scientists patent new quantum processor architecture (in Russian)

Interfax

05/26/2022

Russian scientists patent new quantum processor architecture (in Russian)

Kommersant

05/26/2022

Russian scientists patent quantum computer (in Russian)

RIA NOVOSTI

05/26/2022

Russian scientists have patented a new quantum processor architecture (in Russian)

Seldon.News

05/26/2022

Quantum computer with multi-level cells patented in Russia (in Russian)

Smotrim

05/26/2022

Quantum processor based on multi-level qubits patented in Russia

TASS

05/26/2022

Quantum computer with multi-level cells patented in Russia (in Russian)

VESTI RU

08/25/2020

Leading research centers’ innovations discussed by the Tsifrovaya ekonomika Autonomous Non-profit Organization and Russian Venture Company (in Russian)

CNews

08/25/2020

Leading research centers’ innovations discussed by the Tsifrovaya ekonomika Autonomous Non-profit Organization and Russian Venture Company (in Russian)

Tsifrovaya ekonomika

08/24/2020

The Quantum Computing LRC presents a project to create the first Russian quantum computer and cloud access interface. The prototype expected to appear already in late 2020. The experimental prototype with cloud access said to be presented in 2022 (in Russ

Finansovaya gazeta

08/24/2020

The Quantum Computing LRC presents a project to create the first Russian quantum computer and cloud access interface (in Russian)

Prime

08/24/2020

The Quantum Computing LRC presents a project to create the first Russian quantum computer and cloud access interface (in Russian)

Rambler

08/24/2020

Two programs to create a cloud-based quantum computer and sensor trusted systems being implemented in Russia (in Russian)

TADVISER

Events

21–23 June 2022

QUANTUMatter 2022
Барселона, Испания

1–3 June 2022

CIPR 2022
Nizhny Novgorod

27 May 2022

Startup Village 2022 International Tech Conference
Skolkovo

24–27 May 2022

SaintPetersburg OPEN 2022
Saint Petersburg

4–8 October 2021

International Conference on Micro- and Nanoelectronics – 2021
Zvenigorod

3–9 October 2021

Microelectronics 2021 International Forum
Gurzuf, Crimea

26–30 September 2021

Saratov Fall meeting 2021
Saratov

7–16 September 2021

Schaffhausen Institute of Technology (SIT) workshop 2021
Online

29 September–2 October 2020

Saratov Fall meeting 2020
Saratov

26 September–3 October 2020

Microelectronics 2020 International Forum
Yalta, Crimea

Team

The project is led by a consortium of organizations: Russian Quantum Center (Leading research center for quantum computing — LRC), Lebedev Physical Institute of the Russian Academy of Sciences (LPI RAS),

Skolkovo Institute of Science and Technology (Skoltech) and Valiev Institute of Physics and Technology of the Russian Academy of Sciences (Valiev IPT RAS). Industrial partner of the project is SP Kvant LLC

Development Progress

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Quantum Platform Scheme