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Design Project |
Prof Dirk R. Englund, EECS; englund@mit.edu, office 36-525 Dr Phillip D. Keathley, Research Laboratory of Electronics, pdkeat2@mit.edu, office 36-285 Prof Marc Baldo, EECS; baldo@mit.edu |
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6.2410 | Laboratory in Quantum Systems Engineering | Spring Semester, 2023
6.2410 |Spring Semester, 2023
Laboratory in Quantum Systems Engineering: Quantum Engineering Platforms
Prereqs: 6.2400, 6.6400, 18.435, or (8.04 and 8.05)
Units: 1-5-6
Goal:
Design and implementation of quantum information science and engineering:
(T1) quantum computing
(T2) quantum communications
(T3) quantum sensing and quantum metrology
.. with a focus on these quantum engineering platforms:
(E1) quantum optics with an emphasis on entangled optical photons for enhanced sensing and communication
(E2) quantum computing with an emphasis on superconducting qubits via IBM Qiskit
(E3) and solid state spin systems with a focus on quantum sensing and magnetometry.
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6.2410 |Spring Semester, 2023
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Laboratory platforms / Activities | | Introduction | Goal 1 | Goal 2 | Potential directions for open-ended design lab components at end of semester |
T2E1: Optical_Photons.quantum key distribution | ~ 1 hr recorded lecture and lecture notes, pre-lab questions; lab notebook check-ins and final report. | ||||
Hardware | QuTools QuED station. | ||||
Lab goals & core concepts | | Laser optics laboratory introduction, strong-field quantum key distribution simulator | Attenuated-laser quantum key distribution (QDK) : BB84 protocol | Attenuated-laser QKD with single photon detection --> quantum secure key generation | Advances in error correction, privacy amplification, signal processing, and hardwave variants "measurement-device independent QKD", twin-field QKD |
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T3E1: Optical_Photons.entanglement | ~ 1 hr recorded lecture and lecture notes, pre-lab questions; lab notebook check-ins and final report. | ||||
Hardware | | QuTools Quantenkoffer. | |||
Lab goals & core concepts | | Perform measurements to characterize single-photon states and demonstrate entanglement. | Develop single-photon interferometer and demonstrate interaction-free measurement. | Demonstrate Hong-Ou-Mandel effect and NOON state generation. Explore enhanced metrology with NOON state interferometry. | Quantum sensing with NOON states; demonstration quantum-enhanced sensing; alternative techniques such as squeezed states. |
6.2410 |Spring Semester, 2023
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T3E3: Solid_State_Spins | ~ 1 hr recorded lecture and lecture notes, pre-lab questions; lab notebook check-ins and final report. | ||||
Hardware | NV spin system module (home-built) | ||||
Lab goals & core concepts | | Characterize microwave cavities and Helmholtz coils | Simulate strong coupling between NV centers in diamond and microwave cylindrical resonator | Experimentally achieve strong coupling between NV centers and the microwave cavity via cavity reflection readout | Improving the anti-crossing contrast by optimizing various experimental parameters; estimate best-achievable magnetometry sensitivity |
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T1E2: Quantum computing w/ IBM Qiskit | ~ 1 hr recorded lecture and lecture notes, pre-lab questions; lab notebook check-ins and final report. | ||||
Software | | IBM Qiskit (and potentially others) | |||
Lab goals & core concepts | | Introduction to software tools and methods; quantum circuits | Quantum measurements and teleportation; quantum phase algorithm | Quantum error correction | Qu computing algorithms on cloud device; build room temperature classical quantum simulators with comparison to cloud device/software simulators |
no longer required as we move to design project
6.2410 |Spring Semester, 2023
Writing the research proposal
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6.2410 |Spring Semester, 2023
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6.2410 |Spring Semester, 2023
Possible project for T2E1 + T3E1:
Quantum Optics Project - Implement Experimental Eve’s Sidechannel attack
Major goal: Implement an eavesdropper (Eve) “sidechannel attack” in a quantum key distribution (QKD) system by trying to monitor or control Bob’s APD flash
State of the art: Current QKD systems with various encoding and security techniques
Gap: Detection of eavesdropping attempts and vulnerabilities in QKD systems
Proposed approach: Implement a side-channel attack into a QKD system to simulate an eavesdropping attempt and test the system's security
Targeted key results: Effective detection and countermeasures against eavesdropping attempts & sidechannel attacks in QKD systems
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6.2410 |Spring Semester, 2023
HT2E1 + T3E1: Entangled-photon-pair-heralded BB84
Major goal: Implement heralded BB84 quantum key distribution based on Y. Adachi et al.'s work
State of the art: Standard BB84 QKD protocol and parametric down-conversion techniques
Gap: Efficient and secure quantum key distribution with improved performance
Proposed approach: Develop and test a heralded BB84 QKD system using parametric down-conversion
Targeted key results: Increased efficiency and security in QKD systems
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6.2410 |Spring Semester, 2023
T3E3: Solid_State_Spins - Detailed Noise Analysis
Major goal: Conduct a detailed noise analysis of a custom NV-spin cavity system. Extract cavity thermal noise.
State of the art: Existing noise analysis techniques for solid-state spin systems can have gaps
Gap: Comprehensive understanding of noise sources and their effects on the system's performance
Proposed approach: Measure and analyze the noise spectral density of the custom NV-spin cavity system
Targeted key results: Identification of noise sources and strategies to minimize their impact on system performance, including consideration of “spin cooling”
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6.2410 |Spring Semester, 2023
T3E3: Solid_State_Spins
Machine-Learning-Guided Quantum Sensor Readout
Major goal: Implement a machine-learning-guided (reinforcement learning) quantum sensor readout for NV-spin cavity systems
State of the art: Conventional quantum sensor readout techniques
Gap: Efficient and accurate quantum sensor readout systems
Proposed approach: Develop and test a reinforcement learning-based readout system for NV-spin cavity-based quantum sensors
Targeted key results: Improved quantum sensor readout accuracy and efficiency through machine learning techniques
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6.2410 |Spring Semester, 2023
other project ideas
Advanced control methods (such as flavors of ML, DNNs) for optimal control/ feedback to push the experiments you’ve already done to another level
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6.2410 |Spring Semester, 2023
Machine learning transceivers
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6.2410 |Spring Semester, 2023
Monte Carlo Simulations
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6.2410 |Spring Semester, 2023