QuantERA has secured a dedicated networking space within Ideal-ist (www.ideal-ist.eu/user/register). To search for potential partners and share your project ideas you have to register into and choose proper call identifier, namely: QuantERA Call 2017 for Transnational Research Proposals.
On-going Partner Requests
Ultrafast low-energy all-electronic memory for flux quantum logic
The CDW memory is a disruptive new all-electronic non-volatile memory concept offering low-temperature sub-picosecond non-volatile memristive switching with extremely small programming energy. The memory works on the principle of a topological transformation of charge ordered states caused by charge injection discovered in ultrafast optical studies of non-equilibrium phase transitions.
The project is designed to move the concept from proof-of-concept devices to the prototype stage, demonstrating new memory devices in the area of Quantum Technology for cryo-computing memory, both quantum and classical. Introducing the device to quantum computing applications requires a number of technology steps, the identification of optimal solutions and addressing the market needs for establishing technological feasibility in superconducting computing application. Development of the technology would open the way to explotiation of cryocomputing technology which has so far been blocked by the absence of a suitable ultrafast low-energy cryo-memory. Success in proving the CDW memory concept would give the rise to a paradigm shift and provide new impetus for the enhanced development of ultrafast cryogenic computing.
Quantum-like Approaches for Decision Making Under Uncertainty
An important question is whether simpler and a more generalise probabilistic model can be found using von Neumann probabilities which could improve models in finance, economics.
Such a model is the quantum-like Bayesian network. We will investigate how much more accurate quantum-like Bayesian network are for decision task with incomplete and inconsistent knowledge compared to the classical contra parts. Bayesian Networks are able to automatically learn probabilities through mechanisms such as the maximum likelihood estimate and EM clustering. We will investigate how to map the corresponding methods to quantum-like Bayesian networks. This learning methods have to be extended since von Neumann probabilities have an additional free parameter that corresponds to the phase. Phase contributes only for unknown variables. Furthermore we will extend the models into dynamic quantum-like Bayesian networks that capture time and uncertainty.
Search for high quality qubits in new CMOS architechtures
The objective of this proposal is to develop qubit systems in low dimensional CMOS architectures at sub 10-nm technology nodes. The development of scalable high quality qubit system using point defects, impurities, quantum dots and electron confinement effects will be the main focus of this research. Advanced CMOS technology nodes can offer desired platforms for high quality qubit systems. Controlling of qubit system and reading out quantum state of each qubit require tramendous effort of interfacing quantum and classical world. The fabrication of new CMOS architectures such as fully-depleted SOI and finFET type of structures will provide essential platforms for experimenting systematically and demonstrating related scalable high quality qubit systems and thus offering integration possibilities with Si circuitry.
QuanTest: Building Testing Foundations for Quantum Programming
With the increasing number of Quantum computing platforms (e.g., IBM Quantum Experience) and languages (e.g., QCL and LanQ) for quantum programming, it is becoming imperative to devise novel testing methods to test programs coded in quantum computing languages. Given the nature of quantum programming (e.g., qubits), unobservability of execution information demand the development of radically new testing methods relying on rigorous theoretical foundations. In addition, given the complexity of problems that need to be solved with quantum computing, such testing methods must incorporate optimization algorithms, e.g., multi-objective search algorithms. Needlessly to say, existing algorithms either have to be extended for quantum computing (if possible) or a completely new family of multi-objective search algorithms must be developed based on quantum computing. The research agenda of this proposal is three-folds: 1) building testing foundations for quantum programming, 2) building novel search-based multi-objective test optimization algorithms, and 3) developing an experimental testing framework to support experiments involving testing of quantum programs with the proposed testing foundations and optimization algorithms.
Solving Optimization Problems with Adiabatic Quantum Computation
Solving Integer optimization problems with classical computers is computationally hard. The current Adiabatic quantum computers allows us to solve QUBO problems (Quadratic Unconstrained Binary Optimization), offering us a way to compete in the future with conventional computation. In order to solve mixed optimization problems, new algorithms that take advantage of this new paradigm have to be designed. Those algorithms should be tested with industrial problems in order to evaluate their efficiency compared to the traditional ones.
Mathematical modelling of hybrid classical-quantum networks
Quantum walks on graphs can be used as a simple and very powerful model for the purpose of modelling quantum and hybrid classical-quantum networks. The main objective of this project is to use quantum walks for the purpose of developing new protocols for controlling the networks of quantum processing units connected by quantum channels. This type of networks requires new methods allowing to fully utilise the capabilities offered by quantum information processing. Quantum internetworking protocols should be able to exploit the quantum effects, including quantum teleportation, dense coding and quantum key distribution. These effects operate on classical and quantum data and thus quantum internetworking protocols have to provide the means for operating on both types of data.
Quantum sensing with massive and fast entangled atoms from dissociation of rotationally and vibrationally cold dimers in supersonic beams
Studies of entanglement in a pair of fast and massive atoms created in a process of controlled dissociation of homonuclear diatoms are proposed in order to extends a gallery of “objects” between which creation of entanglement is possible. Outcome of this approach can be used to broaden quantum sensing to atoms that possess rest mass and considerable kinetic energies. Using technique of supersonic molecular beam, methods of laser spectroscopy and stimulated Raman adiabatic passage (STIRAP), quantum entanglement between two atoms possessing antiparallel components of a nuclear atomic angular momentum in a single act of selective molecular dissociation can be created. Analysis of the quantum entanglement will rely on a detection of coincidences of two atoms with antiparallel components of a nuclear atomic angular momentum appearing in two distant detectors localized in so-called planes of detection using a process of spin state selective two-photon excitation-ionization (TPEI). Results of studies of quantum entanglement between atoms “born” from a single dimer would gain interest of scientists investigating tests of quantum mechanics and aspects of quantum sensing with hot (not ultra-cold) and massive (not photons with no rest mass) objects. It will pioneer the way towards better understanding subtleties of quantum information processing and quantum sensing.
Innovation of patient specific quantum learning architecture for enhancing real-time brain-computer interface (BCI)
Design a data-driven non-heuristic learning architecture based on the concepts from quantum mechanics to filter (and enhance) the information from the raw physiological (EEG) signal.
The plan is to make this quantum learning architecture practically applicable (embedding as a System on Chip) for real-time physiological signal filtering, thereby improve the overall accuracy of the Brain-Compter Interface.
Mechanism for quantized fonon transport between graphene layers
This pre-proposal is for a project that has main objective to prepare for a QuantERA Full Proposal by performing preliminary research and testing out methodology necessary to reduce the uncertainties connected to feasibility of approach and methodology.
We will attempt to elucidate key aspects in the mechanism for quantized fonon transport between graphene layers. Through molecular dynamics simulations and quantum chemical calculations of interactions between carbon atoms in graphene and phonons, we will obtain information and improve knowledge of the characteristics of phonon movement when graphene layers are the surrounding material. This encompass elucidation of how phonon transmission is suppressed through application of functionalization constrains, expressed through vibrational and electronic transport properties. Also, we will study the intercalation of molecules that tends to weaken the interlayer coupling of graphene therefore increasing the cross-plane thermal resistance as well as functioning as obstacles for phonon channels.
This is important knowledge in the efforts to improving thermal conductance in graphene, particularily when the graphene is used as the active material in microprocessor cooling technology.
The research to be conducted builds upon and aims to advance the scientific contributions presented in the following two publications:
· Zhang Y, Han H, Wang N, et al (2015) Improved Heat Spreading Performance of Functionalized Graphene in Microelectronic Device Application. Adv Funct Mater. doi: 10.1002/adfm.201500990
· Han H, Zhang Y, Wang N, et al (2016) Functionalization mediates heat transport in graphene nanoflakes. Nature Communications. doi: 10.1038/ncomms11281