BD
B. Dorland
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Quantum networks offer more capabilities than classical networks. For example, quantum networks can solve certain problems faster than classical networks and they can even solve problems which cannot be solved with classical networks. One well-known quantum network application is blind quantum computing (BQC). In a BQC application, a client node sends a computation to a server node in the network. The server node performs this computation without knowing the details about the actual input or computation being performed and returns the result of the computation to the client node. Quantum applications are often repeated many times due to randomness that is involved in the result of executing a quantum application. When a server node performs BQC repeatedly with multiple client nodes, there arises an interesting problem of how all corresponding instructions can be scheduled for the server optimally, given that certain types of instructions referred to as entanglement instructions can only be scheduled at given moments by a so-called network schedule. One classical metric used to assess the quality of a schedule is makespan, which is the time that it takes to complete all instructions. A quantum-oriented metric involved is success probability, which indicates what fraction of executions yield a desired result when repeatedly executing an application. In this thesis, an experimental demonstration is given of the use of constraint programming (CP) for the scheduling of instructions of quantum network applications. This demonstration focuses on scheduling instructions that the server node should execute when performing BQC repeatedly with a small number of client nodes at the same time. Different CP models are presented that assign start times to tasks that the server node should execute. By comparing the CP models to a baseline scheduler that schedules tasks as soon as possible, it was found that CP can be used to reduce the makespan when BQC is performed by the server node with multiple clients at the same time, while preserving a similar success probability. A main drawback that followed from the CP approach is scalability. Future work is to be done on studying how CP can be used for larger quantum networks.
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Quantum networks offer more capabilities than classical networks. For example, quantum networks can solve certain problems faster than classical networks and they can even solve problems which cannot be solved with classical networks. One well-known quantum network application is blind quantum computing (BQC). In a BQC application, a client node sends a computation to a server node in the network. The server node performs this computation without knowing the details about the actual input or computation being performed and returns the result of the computation to the client node. Quantum applications are often repeated many times due to randomness that is involved in the result of executing a quantum application. When a server node performs BQC repeatedly with multiple client nodes, there arises an interesting problem of how all corresponding instructions can be scheduled for the server optimally, given that certain types of instructions referred to as entanglement instructions can only be scheduled at given moments by a so-called network schedule. One classical metric used to assess the quality of a schedule is makespan, which is the time that it takes to complete all instructions. A quantum-oriented metric involved is success probability, which indicates what fraction of executions yield a desired result when repeatedly executing an application. In this thesis, an experimental demonstration is given of the use of constraint programming (CP) for the scheduling of instructions of quantum network applications. This demonstration focuses on scheduling instructions that the server node should execute when performing BQC repeatedly with a small number of client nodes at the same time. Different CP models are presented that assign start times to tasks that the server node should execute. By comparing the CP models to a baseline scheduler that schedules tasks as soon as possible, it was found that CP can be used to reduce the makespan when BQC is performed by the server node with multiple clients at the same time, while preserving a similar success probability. A main drawback that followed from the CP approach is scalability. Future work is to be done on studying how CP can be used for larger quantum networks.
Bachelor thesis
(2020)
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Ruben Band, Koen du Buf, Bob Dorland, Quintin van Leersum, Emma Sala, M.A. Migut
Cityhunter developed the idea of transforming their card game, Hunting Happy Families, into a game that can be played on tablets in a same manner that their other game, Hunt the Hunter, can be played. The aim of this project is to develop a game that can be played in Schiedam on an Android platform. An additional requirement is that the game can be adapted after the project is finished. That is, the client must be able to add new card sets and new locations through an interface without having to make changes in the codebase. Another part of this project includes a gamemaster interface, in which one person can keep track of all teams in a game, including their cards, points, locations and chat messages. Lastly, a server was created for storing and sending information between teams and the game master. This report defines the standard game play of a game of Hunting Happy Families. The main goal of the game is to learn about the history of the city of Schiedam. By walking around, teams can collect cards from other players, and identify locations associated with the various sets to try and gather as many points as possible. The team with the most points at the end of the game, wins. The system features a server connecting the teams and the game master using a string message system and lambda functions. Upon sending a message using this system, the server handles the requested data, and answers the request by forwarding the provided information, or relaying the information requested. The system was thoroughly field tested, including a playtest with external players. The verdict on the game by these players is positive, though the system needs a slight amount of fine tuning to ensure the best experience. That said, the game is completely ready for use, andHuntingHappy Families is bound to carve its niche in the market of group events.
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Cityhunter developed the idea of transforming their card game, Hunting Happy Families, into a game that can be played on tablets in a same manner that their other game, Hunt the Hunter, can be played. The aim of this project is to develop a game that can be played in Schiedam on an Android platform. An additional requirement is that the game can be adapted after the project is finished. That is, the client must be able to add new card sets and new locations through an interface without having to make changes in the codebase. Another part of this project includes a gamemaster interface, in which one person can keep track of all teams in a game, including their cards, points, locations and chat messages. Lastly, a server was created for storing and sending information between teams and the game master. This report defines the standard game play of a game of Hunting Happy Families. The main goal of the game is to learn about the history of the city of Schiedam. By walking around, teams can collect cards from other players, and identify locations associated with the various sets to try and gather as many points as possible. The team with the most points at the end of the game, wins. The system features a server connecting the teams and the game master using a string message system and lambda functions. Upon sending a message using this system, the server handles the requested data, and answers the request by forwarding the provided information, or relaying the information requested. The system was thoroughly field tested, including a playtest with external players. The verdict on the game by these players is positive, though the system needs a slight amount of fine tuning to ensure the best experience. That said, the game is completely ready for use, andHuntingHappy Families is bound to carve its niche in the market of group events.