World Quantum Day Abstracts
Interaction-free measurement and beyond by Suhail Zubairy
It is truly amazing that, even today, an understanding of simple systems can lead to startling new ideas and devices. In this talk I shall discuss how the simplest quantum optical devices like mirrors and beam splitters can be employed in areas such as interaction-free measurement, quantum secure communication, generation of elusive Schrodinger-cat states of the radiation field, and communication with invisible photons.
A Little Chemistry for Quantum in three Dimensions by Tina Brower-Thomas
Self-assembled conjugated pi-systems, such as aromatic thiols, on gold substrates buoyed the field of molecular electronics and offered a unique solution to some of the challenges faced by the semiconductor industry. Another p-system that holds even a greater promise is graphene, a single atom thick layer of carbon atoms. In fact, the impact of the successful exfoliation of graphene from bulk graphite has left an indelible mark on several fields, including condensed matter physics, chemistry, and materials science. Although graphene possesses some promising properties, such as high mobility and high thermal conductivity, graphene’s lack of a bandgap and magnetic properties has impeded its use in a variety of industrial applications, including electronics and spintronics. My group aims to functionalize graphene, improving graphene’s function without fundamentally affecting its desirable properties. Although theoretical reports of graphene’s interaction with transition metal (TM) and alkali ions (AI) show a retention of graphene’s properties upon the adsorption of these atoms, experimental approaches are needed to substantiate these theoretical works. Motivated by a lack of comprehensive experimental work in this field, we have been investigating the interaction of TM and AI with the surface of graphene using chemical and electrochemical reactions. Finally, I am setting up a microwave plasma chemical vapor deposition system that will be coupled to x-ray diffraction at the Brookhaven National Laboratory Synchrotron Source for in-situ x-ray growth studies of diamond growth. In addition to discussing our work in the field, we will also discuss our contributions in quantum education and work force development
Ultimate quantum sensing sensitivity and computational speed up through multiphoton interference with scalable resources by Vincenzo Tamma
Quantum interference is one of the most intriguing phenomena in quantum physics at the very heart of the development of quantum technology in the current quantum industry era. It underpins fundamental tests of the quantum mechanical nature of our universe as well as applications in quantum computing, quantum sensing and quantum communication. I will give an overview of multiphoton sensing techniques enabling the ultimate quantum sensitivity, given by the quantum Cramér-Rao bound, by employing sampling measurements which resolve the inner degrees of freedom, such as time, frequency, position, and polarization, of single photons interfering at a beam splitter [1-4]. This includes: estimation of the transverse displacement between photons and the position of a given source for applications in super-resolved single-molecule localization microscopy, by circumventing the requirements in standard direct imaging of camera resolution at the diffraction limit, and of highly magnifying objectives [1]; multi-parameter estimation of the polarization state of two interfering photonic qubits for applications in quantum information networks [2]; imaging of nanostructures, including biological samples, and nanomaterial surfaces, with arbitrary values of thickness through estimation of photonic time delays [3]; ultimate quantum sensitivity in single-photon spectroscopy based only on sampling time-resolved detections [4]; superresolution imaging beyond the Rayleigh limit of incoherent sources via two-photon interference sampling measurements in the transverse momenta [5]. I will also describe how the metrological power of quantum interference of single photons is intimately connected with an exponential speed-up in quantum optical networks, particularly in the development of scalable boson sampling experiments [6,7]. Finally, I will show novel quantum interference techniques based on linear optical networks with squeezed light for the measurements with Heisenberg-scaling sensitivity of a single parameter [8] or multiple parameters [9]. Applications can range from environmental sensing to high-precision biomedical imaging, characterization of nanomaterials, navigation, gravity tests and quantum networks of high-precision clocks. This research opens a new paradigm based on the interface between the physics of quantum interference, quantum sensing and quantum exponential speed-up with experimentally feasible “real world” photonic sources
[1] D. Triggiani and V. Tamma, Phys. Rev. Lett. 132, 180802 (2024), D. Triggiani and V. Tamma, Phys. Rev. A 111, 032605 [2] L. Maggio, D. Triggiani, P. Facchi, and V. Tamma, Physica Scripta 100, 035106 (2025) [3] D. Triggiani, G. Psaroudis, V. Tamma, Phys. Rev. Applied 19, 044068 (2023) [4] L. Maggio, D. Triggiani, P. Facchi, and V. Tamma, arXiv:2412.16304 (2024) [5] S. Muratore, D. Triggiani and V. Tamma, arXiv:2412.10057 (2024) [6] V. Tamma and S. Laibacher, Eur. Phys. J. Plus 138, 335 (2023), V. Tamma and S. Laibacher, Phys. Rev. A 104, 032204 (2021); S. Laibacher and V. Tamma, Phys. Rev. A 98, 053829 (2018); V. Tamma and S. Laibacher, Phys. Rev. Lett. 114, 243601 (2015); S. Laibacher and V. Tamma, Phys. Rev. Lett. 115, 243605 (2015) [7] X.-J. Wang et al., Phys. Rev. Lett. 121, 080501 (2018); V. V. Orre, et al. Phys. Rev. Lett. 123, 123603 (2019) [8] D. Gatto, P. Facchi and V. Tamma, Phys. Rev. A 105, 012607 (2022); G. Gramegna et al. New J. of Physics 23, 053002 (2021); G. Gramegna et al. Phys. Rev. Research 3, 013152 (2021); D. Triggiani, P. Facchi, and V. Tamma, Phys. Rev. A 104, 062603 (2021); D. Gatto, P. Facchi and V. Tamma, Phys. Rev. Research 1, 032024 (2019) [9] A. Rai, D. Triggiani, P. Facchi and V. Tamma, arXiv:2405.17115 (2024)
Scaling optimization with hybrid quantum-classical algorithms by Ilya Safro
Emerging quantum processors offer new opportunities to explore innovative approaches for solving optimization problems in the post-Moore’s law era. However, even with the optimistic expectations regarding building nearly fault-tolerant quantum processors, the limited number of qubits will still make it infeasible to directly tackle massive real-world problems in the near future which reminds the early days of scientific computing and high- erformance computing architectures. This presents significant challenges in leveraging these quantum processors for practical applications. Hybrid quantum-classical algorithms, which combine the strengths of both quantum and classical devices, are considered one of the most promising strategies for applying quantum computing to optimization and machine learning problems. In this talk, we will discuss several approaches for designing such algorithms, with a particular focus on multigrid-inspired frameworks for large-scale combinatorial optimization as a flexible paradigm for hybrid quantum-classical algorithms. We will discuss the integration of these frameworks with the Quantum Approximate Optimization Algorithm (QAOA), enhanced with techniques such as graph representation learning, variational parameter transferability, and recursive QAOA, highlighting their potential to improve scalability and quality of quantum approaches.
Relevant papers:
Hayato Ushijima-Mwesigwa, Ruslan Shaydulin, Susan Mniszewski, Christian Negre, Yuri Alexeev, Ilya Safro “Multilevel Combinatorial Optimization Across Quantum Architectures”, ACM Transactions on Quantum Computing, Vol. 2(1), pp. 1-29, 2021, preprint at https://arxiv.org/abs/1910.09985
Jose Falla, Quinn Langfitt, Yuri Alexeev, Ilya Safro “Graph Representation Learning for Parameter Transferability in Quantum Approximate Optimization Algorithm”, Quantum Machine Intelligence, vol. 6, num. 46, preprint at https://arxiv.org/abs/2401.06655, https://doi.org/10.1007/s42484-024-00178-9, 2024
Bao Bach, Jose Falla, Ilya Safro “MLQAOA: Graph Learning Accelerated Hybrid Quantum-Classical Multilevel QAOA”, IEEE Quantum Computing and Engineering (best paper award), preprint at https://arxiv.org/pdf/2404.14399, 2024
Alexey Galda, Eesh Gupta, Jose Falla, Xiaoyuan Liu, Danylo Lykov, Yuri Alexeev, Ilya Safro “Similarity-Based Parameter Transferability in the Quantum Approximate Optimization Algorithm”, accepted in Frontiers in Quantum Science and Technology (section Quantum Information Theory), DOI: 10.3389/frqst.2023.1200975, 2023
Original QAOA paper: Farhi, Edward, Jeffrey Goldstone, and Sam Gutmann. “A quantum approximate optimization algorithm.” arXiv preprint arXiv:1411.4028 (2014).
Classical computing background: Dorit Ron, Ilya Safro, Achi Brandt “Relaxation-based coarsening and multiscale graph organization”, SIAM Multiscale Modeling and Simulations, Vol. 9, No. 1, pp. 407-423, 2011, https://www.eecis.udel.edu/~isafro/papers/relax-coarsening-graphs.pdf