Efficient detection of single-photon emission is a vital aspect in the design of quantum computers based on color centers in diamond. SNSPD’s are the best candidate for this purpose, showing high detection efficiencies in combination with a low dark-count rate. ​

Typically, SNSPD’s and qubits are separated from each other, connected by optical fibers. The goal, however, is to integrate all subsystems of the quantum computer on a single chip, which includes the SNSPD’s. On-chip fiber connections are, of course, not practical, so waveguide structures are used instead. SNSPD’s are placed on top of these structures. As the light travels through the waveguides, the photons are absorbed by the nanowire, resulting in a detection event. ​

Integration of many subsystems on a single chip necessitates footprint reduction of individual components. In an integrated quantum computer, based on defects in diamond, every qubit has multiple SNSPD’s. Reducing the footprint of individual SNSPD’s could potentially significantly reduce the footprint of the whole system.

Project: SNSPD’s on top of optical cavity for footprint reduction
In this project, you will do the following:

• Design of optical waveguide cavity
• Fabrication of the waveguide-integrated SNSPD’s in a cleanroom
• Measurement and characterization of the SNSPD’s

Join the project:

If you are interested to join this project, please contact Salahuddin Nur or Ryoichi Ishihara.

Mechanical oscillators are used in a wide range of applications as force and inertial sensors. The use of a levitated mechanical oscillator based on magnetostatic fields avoids multiple losses and problems other systems have. Combining this with a nitrogen-vacancy (NV) center to create strong spin-mechanical coupling is a promising candidate for quantum sensing, quantum communication and ultra-sensitive magnetometry. ​

The oscillator consists of a micromagnet contained in a silicon pocket that is levitated with a type II superconductor. The lid of this pocket is a diamond containing NV centers for spin-mechanical coupling. NV centers are fluorescent and when coupled to the magnet the intensity depends on the magnets position. Displacements can thus be precisely determined by measuring the fluorescence of the NV center. ​

In this research, micro-magnets that range from 1 to 100 μm are levitated with the use of a type II superconductor. The Q-factor, trapping frequencies and coupling strength will be measured for the different sizes of micro-magnets.

Project: Characterization of the levitation properties of micro-magnets of different sizes + coupling to electron spin
In this project, you will do the following:

• Place micro-magnets into small pockets using a pick-and-place system
• Levitate the micro-magnets in a cryostation, and observe the levitation properties with a camera
• Couple the mechanical oscillations of the micromagnet to the spin on an electron in an NV center.

Join the project:

If you are interested to join this project, please contact Salahuddin Nur or Ryoichi Ishihara.

Nanophotonic cavities are a special type of optical resonators which have dimensions in the order of tens to hundreds of nanometers. They are usually implemented with incorporating Bragg reflectors/controlled index variations in the photonic structures. Nanophotonic cavities can strongly confine light/photon, and thus, can significantly enhance photon generation and collection probability from any emitter placed inside the cavity. This unique properties can be used for enhancing the radiative decay rate of a diamond color center emitter, suppressing non-favorable transitions, improving the coherence and spectral purity, spin-photon entanglement generation efficiency, etc. All of these are critical for efficient qubit readout, remote entanglement and large scale diamond based quantum computer, network system implementation. However, fabricating such nanophotonic cavities accurately in diamond and coupling the color center emitters spatially and spectrally with such cavities are highly challenging. Furthermore, a large scale fabrication and high-yield emitter-cavity coupling process has to be developed in order to realize a scalable, on-chip quantum system, where thousands of qubits can be interconnected and entangled efficiently for useful quantum computing.

Tin-vacancy (SnV) centers in diamond is particularly promising for large scale integration of quantum systems because of their charge noise insensitivity due to inversion symmetry, narrow-linewidth and larger ZPL emission (DW factor ~ 0.57), good compatibility of coupling with nanophotonic structures, long spin coherence times at temperatures above 1 K etc.

Hence, developing an integration process for large scale SnV center-cavity coupled system will be a critical step towards the realization of a useful quantum computer and network. In this project, we plan to research and develop efficient, large scale fabrication & coupling techniques for SnV center-cavity systems, which will open the route to scalable, on-chip integration of thousands of qubits in a quantum node/module. Devising a cavity design tolerant to fabrication imperfections and non-optimal emitter positioning can improve the coupling efficiency with simpler fabrication processes. The proposed fabrication processes will allow spatial tuning (placing emitter at field maxima and dipole aligning) of the cavity-emitter system through deterministic cavity fabrication and ion implantation.

[1]. Alison E. Rugar, and et al., Quantum Photonic Interface for Tin-Vacancy Centers in Diamond, Physical Review X, 11, 031021 (2021)

[2]. Maximilian Ruf, and et al., Quantum networks based on color centers in diamond, Journal of Applied Physics 130, 070901 (2021)

[3]. Noel H. Wan*, Tsung-Ju Lu and et al., Large-scale integration of artificial atoms in hybrid photonic circuits, Nature 583, 226–23 (2020).

[4]. Andreas Reiserer, Colloquium : Cavity-enhanced quantum network nodes, Rev. Mod. Phys. 94 041003 (2022)

[5]. Johannes Görlitz, and et al., Spectroscopic investigations of negatively charged tin-vacancy centres in diamond, New J. Phys. 22, 013048 (2020).

[6]. Takayuki Iwasaki, and et al., Tin-Vacancy Quantum Emitters in Diamond, Phys. Rev. Lett. 119, 253601 (2017)

Join the project:

If you are interested to join this project, please contact Salahuddin Nur or Ryoichi Ishihara.

Quantum sensors can detect magnetic fields and other physical quantities, with unprecedented spatial resolution and sensitivity. A diamond color center based quantum sensing system, when integrated with photonics and electronics, can provide high sensitivity along with compactness and robustness. Such an on-chip, solid-state system will be very attractive for various fields ranging from biomedical to extreme environment applications [1-3]. The performance of the sensors is expected to be improved by making photonic cavity structure in the diamond connected with carefully designed photonic components, integrating deterministic photon sources, and single-photon detectors etc. Coupling the color center qubits with such a photonic network, the measurement precision of a quantum metrology system can be pushed beyond the standard quantum limit (SQL) by using entangled quantum sensors, which has been demonstrated recently with diamond color center based quantum sensors [4].

A system using levitated mircomagnet combined with the quantum sensor using diamond color center can be used to comprise an entangled quantum sensors network. In this scheme, a small magnetic particle will be levitated in a MEMS cavity in a silicon with a strong magnetic field by superconducting coil and color-center in diamond will be coupled gyroscopically with the motion of the particle. Levitated microobject is in general reported to provide a very high Q factor because of the completely isolated system. Theoretical study of the system operating at a cryogenic temperature of 4K predicts a very high sensitivity (approaching 10¹³m/s²/Hz^1/2). The measurement precision of such a quantum metrology system can be pushed beyond the standard quantum limit (SQL) by using entangled quantum sensors. Recently, this has been demonstrated with diamond color center based quantum sensors [5, 6].

In this project, we design a suitable quantum photonic integrated circuit (QuPIC) for diamond color center spins, with which an on-chip, programmable quantum metrology system can be implemented. and Heisenberg-limited sensing precision can be approached. Furthermore, we will design diamond nanophotonic cavities to couple with levitated micromagnets as a step towards an on-chip, integrated and programmable quantum inertial sensor system. Such an inertial sensor system will enable a performance close to the fundamental quantum limit, compact form factor & robust design – fulfilling very well the stringent requirements for space applications.

[1]. C. L. Degen, and et al., Quantum sensing, Rev. Mod. Phys. 89, 035002 (2017)

[2]. S. B.-Esfahani, and et al., Integrated quantum photonic sensor based on Hong-Ou-Mandel interference, Opt. Express 23, 16008-16023 (2015)

[3] N. Aslam, and et al., Quantum sensors for biomedical applications, Nature Reviews Physics (2023)

[4]. T. Xie, and et al., Beating the standard quantum limit under ambient conditions with solid-state spins, Vol. 7, No. 32, (2021)

[5]. V. Cimini, and Et al., Deep reinforcement learning for quantum multiparameter estimation, Advanced Photonics, Vol. 5, Issue 1, 016005 (2023)

[6]. J. Gieseler, and et al., Single-Spin Magnetomechanics with Levitated Micromagnets, Phys. Rev. Lett. 124, 163604 (2020)

Join the project:

If you are interested to join this project, please contact Salahuddin Nur or Ryoichi Ishihara.

Artificial Neural Networks (ANNs) are a type of machine learning algorithm that are inspired by the structure and function of the human brain. In the field of image classification, ANNs are used to identify and categorize objects or scenes within an image. ANNs are composed of interconnected nodes, or “neurons,” that process and transmit information. Each neuron receives input from multiple other neurons, processes the information, and then transmits the output to other neurons in the network. In this way, ANNs can recognize complex patterns and relationships within data. In the context of image classification, the input to an ANN is typically an array of pixel values that represent an image. The ANN then processes this information, using multiple hidden layers, to produce an output class label that indicates which object or scene is present in the image. To train an ANN for image classification, a large labeled dataset of images is used to teach the network how to recognize different objects or scenes. The network’s output is then compared to the actual class labels and the weights of the connections between neurons are adjusted to minimize the error. ANNs are a powerful tool for image classification tasks, allowing computers to automatically recognize and categorize objects in images with high accuracy.

[1] F. Cai, J.M. Correll, S.H. Lee, Y. Lim, V. Bothra, Z. Zhang, M.P. Flynn, W.D. Lu, A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations, Nature Electronics, 2 (2019) 290-299.

Join the project:

If you are interested to join this project, please contact Salahuddin Nur or Ryoichi Ishihara.