Quantum circuits for the Ising spin networks

Spin network states are a powerful tool for constructing the SU(2) gauge theories on a graph. In loop quantum gravity (LQG), they have yielded many promising predictions, although progress has been limited by the computational challenge of dealing with high-dimensional Hilbert spaces. To explore more general configurations, quantum computing methods can be applied by representing spin network states as quantum circuits. In this article, we introduce an improved method for constructing quantum circuits for 4-valent Ising spin networks, which utilizes a smaller number of qubits than previous approaches. This has practical implications for the implementation of quantum circuits. We also demonstrate the procedure with various examples, including the construction of a 10-node Ising spin network state. The key ingredient of the method is the variational transfer of partial states, which we illustrate through numerous examples. Our improved construction provides a promising avenue for further exploring the potential of quantum computing methods in quantum gravity research

Quantum simulations of a qubit of space

In loop quantum gravity approach to Planck scale physics, quantum geometry is represented by superposition of the so-called spin network states. In the recent literature, a class of spin networks promising from the perspective of quantum simulations of quantum gravitational systems has been studied. In this case, the spin network states are represented by graphs with four-valent nodes, and two dimensional intertwiner Hilbert spaces (qubits of space) attached to them. In this article, construction of quantum circuits for a general intertwiner qubit is presented. The obtained circuits are simulated on 5-qubit (Yorktown) and 15-qubit (Melbourne) IBM superconducting quantum computers, giving satisfactory fidelities. The circuits provide building blocks for quantum simulations of complex spin networks in the future. Furthermore, a class of maximally entangled states of spin networks is introduced. As an example of application, attempts to determine transition amplitudes for a monopole and a dipole spin networks with the use of superconducting quantum processor are made.Comment: 17 pages. Matches the version published in PR

Approximate Quantum Compiling for Quantum Simulation: A Tensor Network based approach

The simulation of quantum spin chains is a promising candidate for the demonstration of quantum advantage. One of the main obstacles to achieving this is the noise that arises from implementing the deep circuits that appear in standard quantum time evolution algorithms. Compiling these deep circuits into shallower ones is thus a key issue that we address in this work. We use a Tensor Network based approach to Approximate Quantum Compiling to produce short depth quantum circuits that simulate the time evolution of the Heisenberg spin chain on up to 100 qubits. Furthermore, we run these short depth circuits on a ibmq-mumbai - a 27 qubit device - and show that the accuracy of the measured observables is significantly improved after applying our Tensor Network compilation scheme

Magnetic Cellular Nonlinear Network with Spin Wave Bus for Image Processing

We describe and analyze a cellular nonlinear network based on magnetic nanostructures for image processing. The network consists of magneto-electric cells integrated onto a common ferromagnetic film - spin wave bus. The magneto-electric cell is an artificial two-phase multiferroic structure comprising piezoelectric and ferromagnetic materials. A bit of information is assigned to the cell's magnetic polarization, which can be controlled by the applied voltage. The information exchange among the cells is via the spin waves propagating in the spin wave bus. Each cell changes its state as a combined effect of two: the magneto-electric coupling and the interaction with the spin waves. The distinct feature of the network with spin wave bus is the ability to control the inter-cell communication by an external global parameter - magnetic field. The latter makes possible to realize different image processing functions on the same template without rewiring or reconfiguration. We present the results of numerical simulations illustrating image filtering, erosion, dilation, horizontal and vertical line detection, inversion and edge detection accomplished on one template by the proper choice of the strength and direction of the external magnetic field. We also present numerical assets on the major network parameters such as cell density, power dissipation and functional throughput, and compare them with the parameters projected for other nano-architectures such as CMOL-CrossNet, Quantum Dot Cellular Automata, and Quantum Dot Image Processor. Potentially, the utilization of spin waves phenomena at the nanometer scale may provide a route to low-power consuming and functional logic circuits for special task data processing

Spin-texture topology in curved circuits driven by spin-orbit interactions

Interferometry is a powerful technique used to extract valuable information about the wave function of a system. In this work, we study the response of spin carriers to the effective field textures developed in curved one-dimensional interferometric circuits subject to the joint action of Rashba and Dresselhaus spin-orbit interactions. By using a quantum network technique, we establish that the interplay between these two non-Abelian fields and the circuit's geometry modify the geometrical characteristics of the spinors, particularly on square circuits, leading to the localisation of the electronic wave function and the suppression of the quantum conductance. We propose a topological interpretation by classifying the corresponding spin textures in terms of winding numbers.Comment: 13 pages, 9 figure

All you need is spin: SU(2) equivariant variational quantum circuits based on spin networks

Variational algorithms require architectures that naturally constrain the optimisation space to run efficiently. In geometric quantum machine learning, one achieves this by encoding group structure into parameterised quantum circuits to include the symmetries of a problem as an inductive bias. However, constructing such circuits is challenging as a concrete guiding principle has yet to emerge. In this paper, we propose the use of spin networks, a form of directed tensor network invariant under a group transformation, to devise SU(2) equivariant quantum circuit ans\"atze -- circuits possessing spin rotation symmetry. By changing to the basis that block diagonalises SU(2) group action, these networks provide a natural building block for constructing parameterised equivariant quantum circuits. We prove that our construction is mathematically equivalent to other known constructions, such as those based on twirling and generalised permutations, but more direct to implement on quantum hardware. The efficacy of our constructed circuits is tested by solving the ground state problem of SU(2) symmetric Heisenberg models on the one-dimensional triangular lattice and on the Kagome lattice. Our results highlight that our equivariant circuits boost the performance of quantum variational algorithms, indicating broader applicability to other real-world problems.Comment: 36+14 page

The Fraunhofer Quantum Computing Portal - www.qc.fraunhofer.de - A web-based Simulator of Quantum Computing Processes

Fraunhofer FIRST develops a computing service and collaborative workspace providing a convenient tool for simulation and investigation of quantum algorithms. To broaden the twenty qubit limit of workstation-based simulations to the next qubit decade we provide a dedicated high memorized Linux cluster with fast Myrinet interconnection network together with a adapted parallel simulator engine. This simulation service supplemented by a collaborative workspace is usable everywhere via web interface and integrates both hardware and software as collaboration and investigation platform for the quantum community. The beta test version realizes all common one, two and three qubit gates, arbitrary one and two bit gates, orthogonal measurements as well as special gates like Oracle, Modulo function, Quantum Fourier Transformation and arbitrary Spin-Hamiltonians up to 31 qubits. For a restricted gate set it feasible to investigate circuits with up to sixty qubits. URL: http://www.qc.fraunhofer.d

Neural network agent playing spin Hamiltonian games on a quantum computer

Quantum computing is expected to provide new promising approaches for solving the most challenging problems in material science, communication, search, machine learning and other domains. However, due to the decoherence and gate imperfection errors modern quantum computer systems are characterized by a very complex, dynamical, uncertain and fluctuating computational environment. We develop an autonomous agent effectively interacting with such an environment to solve magnetism problems. By using the reinforcement learning the agent is trained to find the best-possible approximation of a spin Hamiltonian ground state from self-play on quantum devices. We show that the agent can learn the entanglement to imitate the ground state of the quantum spin dimer. The experiments were conducted on quantum computers provided by IBM. To compensate the decoherence we use local spin correction procedure derived from a general sum rule for spin-spin correlation functions of a quantum system with even number of antiferromagnetically-coupled spins in the ground state. Our study paves a way to create a new family of the neural network eigensolvers for quantum computers.Comment: Local spin correction procedure was used to compensate real device errors; comparison with variational approach was adde

A quantum circuit architecture based on the integration of nanophotonic devices and two-dimensional molecular network

Recently both experimental and theoretical works have shown optically addressable molecular spins could have a great potential for quantum information processing. Experimental works such as spin qubit initialisation, coherence control, and readout suggest spin-bearing molecules can be a great candidate for quantum computing. Time-resolved electron spin resonance on molecular radicals at high temperature indicates molecular spins could be the cornerstones for high-temperature quantum gate operations, thus overcoming the low-temperature technical barrier for maintaining quantum circuits effectively. In this proceeding, we have discussed the potential of molecular materials, especially two dimensional molecular network, for optically driven quantum information processing, in combination with nanophotonic devices. Although this is only a theoretical proposal, we hope this can be inspiring for the future development of quantum computing. Obviously there are many difficulties on the way forward, such as single spin readout in molecules, optimal design of molecular networks and corresponding optical instruments, which are be solved in the future