» IQS Seminar Series

Fall 2024 Speaker Schedule:

Wednesday, September 4th - Robert Czupryniak, University of Rochester

Wednesday, September 18th - Eli Levenson Falk, University of Southern California

Wednesday, September 25th - Ariel Ashkenazy, Bar-Ilan University 

Wednesday, October 2nd - Alok Singh, Chapman University & Rochester University 

Wednesday, October 23rd - Abhaya Hedge, University of Rochester

Wednesday, October 30th - Irwin Huang, Chapman University 

Wednesday, November 6th - Shengshi Pang, University of Rochester 

Wednesday, November 13th - Abhishek Chakraborty, Chapman University & University of Rochester  

Wednesday, November 20th - Paolo Andrea Erdman, Freie Universitat Berlin

Wednesday, December 4th - Daniel Briseno Servin, Chapman University

Wednesday, December 11th - Kagan Yanik, Chapman University 

 

Artificially intelligent Maxwell’s demon for optimal control of open quantum systems by Robert Czrupryniak

Wednesday, September 4th @ 10:00am PST in KC 149 or Join us on Zoom

Abstract: Feedback control of open quantum systems is of fundamental importance for practical applications in various contexts, ranging from quantum computation to quantum error correction and quantum metrology. However, deriving optimal feedback control strategies is highly challenging, as it involves the optimal control of open quantum systems, the stochastic nature of quantum measurement, and the inclusion of policies that maximize a long-term time- and trajectory-averaged goal.

In this work, we employ a reinforcement learning approach to automate and capture the role of a quantum Maxwell’s demon: a neural network takes the literal role of discovering optimal control-feedback strategies in qubit-based quantum systems that maximize a tradeoff between measurement-powered cooling and measurement efficiency. We explore different operational regimes based on the ordering between the thermalization, the measurement, and the unitary feedback timescales, finding different and highly non-intuitive, yet interpretable, strategies.

Beating the Ramsey limit on sensing with Hamiltonian control by Eli Levenson-Falk

Wednesday, September 18th @ 10:00am PST or Join us on Zoom

Abstract: Since its invention in 1950, Ramsey interferometry has been the gold standard for measurement of a qubit's frequency. This measurement forms the basis of many quantum sensing protocols and quantum computing gate calibrations. Unfortunately, decoherence limits the sensitivity of this frequency measurement. I will present our recent results deriving and demonstrating a protocol for unconditionally enhancing the signal-to-noise ratio of a qubit frequency measurement. Our protocol uses strictly deterministic Hamiltonian control to stabilize one component of the qubit state, preserving coherence and allowing the sensing signal to grow. We show that it is possible to improve SNR per measurement shot by up to a factor of 1.96 and SNR per evolution time by up to a factor of 1.18, and experimentally demonstrate improvement factors of 1.6 and 1.1 in a superconducting transmon qubit. The protocol requires no extra experimental resources and can be applied in a wide variety of qubit systems. I will discuss possible extensions of our results to further enhance sensitivity.

Photon Number Splitting Attack – Proposal and Analysis of an Experimental Realization based on Single-Photon Raman Interaction by Ariel Ashkenazy

Wednesday, September 25th @ 10:00am PST in KC 149 or Join us on Zoom

Abstract: Photon-number-splitting (PNS) has long been considered a theoretical attack on quantum key distribution (QKD) beyond current technological capabilities. We present an experimental scheme for a PNS attack using demonstrated technological capabilities,
namely a single-photon Raman interaction (SPRINT) in a cavity-enhanced atomic system.
Our analysis shows that the attack results in a small but non-zero quantum bit error,
challenging previous assumptions. We also calculate the eavesdropper’s information
gain and compare our findings with earlier theoretical analyses.

Thermoelectric effects due to particle-hole symmetry breaking near Abrikosov vortices by Alok Singh

Wednesday, October 2nd @ 10:00am PST in KC 149 or Join us on Zoom! 

Abstract: Under the influence of a sufficiently high magnetic field, a type-II superconductor enters a mixed state of normal-metal-like Abrikosov vortices and superconductor-like bulk. Near the vortices, the electronic excitations satisfy Bogoliubov-de Gennes (BdG) equations which are solved numerically in a self-consistent manner. BdG equations imply that the particle-hole symmetry is broken near the vortex core, in the quantum limit, as it introduces a non-trivial topology to the system. I will present a manifestation of this asymmetry in the local density of states. The asymmetry can be exploited to produce a large thermoelectric response when the material is put in conjunction with either a normal metal (NIS junction) or an STM-tip probe. We will first look at the devices' linear thermoelectric response in the form of Seebeck coefficient, electrical/thermal conductivities, power factor, and figure of merit. Then, we will discuss their non-linear thermoelectric response in the form of thermovoltage and IV characteristic. We will also discuss how we can use these devices to build low-temperature thermocouples, diodes, or bolometers.


Time-resolved Stochastic Dynamics of Quantum Thermal Machines by Abhaya Seetaram Hedge

Wednesday, October 23rd @ 10:00am PST Join us on Zoom! This talk is virtual. 

AbstractSteady-state quantum thermal machines are typically characterized by a continuous flow of heat between different reservoirs. At the stochastic level, however, this flow can be unraveled as discrete quantum jumps, each representing an exchange of finite quanta with the environment. We introduce a framework that resolves these dynamics into cycles, classified as engine-like, cooling-like, or idle. By analyzing the statistics and duration of each cycle type, we determine the fraction of cycles useful for thermodynamic tasks and the average waiting time between cycles. This approach offers a new perspective on thermal machines, with direct relevance to modern experiments, such as mesoscopic transport in quantum dots.

Symmetrically Threaded SQUIDs As Next Generation Kerr-cat Qubits by Irwin Huang

Wednesday, October 30th @10:00am PST in KC 149 or Join us on Zoom

Abstract:Kerr-cat qubits are bosonic qubits with autonomous protection against bit-flips. They have been studied widely using driven Superconducting Nonlinear Asymmetric Inductive eLement (SNAIL) oscillators. We theoretically investigate an alternate circuit for the Kerr-cat qubit, namely Symmetrically Threaded SQUIDs (STS). We find that the lifetime time of the coherent states (Tα) of the Kerr-cat qubit is the same in both the STS and SNAIL circuits for weak Kerr nonlinearity. However, the STS Kerr-cat qubits have the additional benefit of being resistant against higher order photon dissipation effects, resulting in significantly longer Tα even with stronger Kerr nonlinearity on the order of 10 MHz. With the proposed design and considering a cat size of 10 photons, we predict Tα of the order of tens of milliseconds even in the presence of multi-photon heating and dephasing effects. The robustness of the STS Kerr-cat qubit makes it a promising component for fault-tolerant quantum processors.

Quantum-limited superresolution for two arbitrary incoherent point sources: beating the resurgence of Rayleigh’s curse by Shengshi Pang

Wednesday, November 6th @ 10:00am PST in KC 149 or Join us on Zoom

Abstract: Superresolution has been demonstrated to overcome the limitation of the Rayleigh's criterion in resolving two incoherent optical point sources. However, in recent years it was found that the Rayleigh’s curse may resurge if the photon numbers of two incoherent optical sources are unknown and have a gap. In this talk, we first analyze the influence of the photon number gap on quantum superresolution for two incoherent sources with the same point-spread function, and show that when the gap of photon numbers is sufficiently small, the superresolution can still be realized but with a slightly decreased precision. Then we extend the superresolution to two incoherent optical sources with different point-spread functions, and show that the competition between the gap of photon numbers, the difference of point-spread functions and the separation of source locations determines the precision of superresolution. The result characterizes the work condition of quantum superresolution, and shows that the superresolution can be realized in a broader regime than previously known.

Two-qubit gates for fluxonium qubits using a tunable coupler by Abhishek Chakraborty

Wednesday, November 13th @ 10:00am PST on Zoom!

Abstract: Tunable couplers enable the realization of efficient two-qubit gates with a high on/off coupling ratio and reduced crosstalk within a single design. In this work, we theoretically explore designs for fast, high-fidelity two-qubit gates between superconducting fluxonium qubits using an inductive tunable coupler. We use this coupler to realize gates from the f-Sim family using fast-flux control on the coupler and qubits.

Machine Learning Methods for Quantum Thermal Devices by Paolo Andrea Erdman

Wednesday, November 20th @ 10:00am in KC 149 or Join us on Zoom! 

Abstract: In the past years, machine learning applications in the field of quantum physics and quantum technologies have surged along various directions. For instance, Machine Learning (ML) has been used for quantum state tomography, quantum state representation, to approximate quantum dynamics, and to design quantum optics experiments [1]. 

In this presentation, we focus on machine learning methods for the optimal control and optimal design of quantum devices in the field of quantum thermodynamics.
First, we discuss how Reinforcement Learning provides a flexible framework for a variety of optimal control problems in non-equilibrium quantum thermodynamics. After reviewing the general framework, we showcase its flexibility optimizing the power-efficiency tradeoff of a quantum thermal machine [2,3], including measurements and feedback [4], and the charging power and ergotropy of a quantum battery that exhibits a collective speedup of the charging power [5]. In all cases, novel control strategies are discovered that outperform previous proposals made in literature. 
We then discuss how gradient-based optimization methods, commonly employed in ML, can lead to the optimal design of quantum devices for quantum thermodynamics, such as the discovery of optimal thermometers using spin networks [6].
REFERENCES:
[1] M. Krenn, J. Landgraf, T. Foesel, and F. Marquardt, Phys. Rev. A 107, 010101 (2023).
[2] P.A. Erdman and F. Noé, NPJ Quantum Inf. 8, 1 (2022).
[3] P.A. Erdman and F. Noé, PNAS Nexus 2, pgad248 (2023).
[4] P.A. Erdman, R. Czupryniak, B. Bhandari, A.N. Jordan, F. Noé, J. Eisert, and G. Guarnieri, arXiv:2408.15328 (2024).
[5] P.A. Erdman, G. M. Andolina, V. Giovannetti, and F. Noé, arXiv:2212.12397, accepted in Phys. Rev. Lett. (2024).
[6] P. Abiuso, P.A. Erdman, M. Ronen, F. Noé, G. Haack, and M. Perarnau-Llobet, Quantum Sci. Technol. 9 035008 (2024).