Guus Avis, UMass-Amherst

Title: Optimization of Quantum-Repeater Networks using Stochastic Automatic Differentiation

Abstract: Quantum repeaters are envisioned to enable long-distance entanglement distribution. Analysis of quantum-repeater networks could hasten their realization by informing design decisions and research priorities. Determining derivatives of network properties is crucial towards that end, facilitating optimizations and revealing parameter sensitivity. Doing so, however, is difficult because the networks are discretely random. Here we use a recently developed technique, stochastic automatic differentiation, to automatically extract derivatives from discrete Monte Carlo simulations of repeater networks. With these derivatives, we optimize rate-fidelity tradeoffs in a repeater chain, determine the chain's sensitivity with respect to the coherence times of different nodes, and finally choose the locations of quantum repeaters in a two-dimensional plane to optimize the guaranteed quality of service between four end nodes. In particular, the technique enabled us to discover the best achievable quality of service, the minimal number of repeaters required to improve a network, and the number of repeaters required to saturate the network scale with the physical size of the network.

Emma Batson, MIT

Title: Fluctuations in Magnesium Diboride

Abstract: Quantum networks need high-efficiency, sensitive detectors such as superconducting nanowire single photon detectors (SNSPDs). Existing devices, however, often have a low operating temperature. Magnesium diboride (MgB2) has a high transition temperature, critical current, and field, but its performance in SNSPDs is not well understood. Through close study of the material physics of magnesium diboride, we can develop techniques for improved SNSPDs in MgB2 and thus expand SNSPD operation to more extreme environments. Here we present data on the fluctuation rate of magnesium diboride devices of different widths and at different operating temperatures, and compare it qualitatively to the theory of fluctuations in isotropic, single-gap superconductors

Jason Han, REU

Title: EnQode: Efficient Amplitude Embedding for Quantum Machine Learning

Abstract: Amplitude embedding (AE) is essential in quantum machine learning (QML) for encoding classical data onto quantum circuits. However, conventional AE methods suffer from deep, variable-length circuits that introduce high output error due to extensive gate usage and variable error rates across samples, resulting in noise-driven inconsistencies that degrade model accuracy. We introduce EnQode, a fast AE technique based on symbolic representation that addresses these limitations by clustering dataset samples and solving for cluster mean states through a low-depth, machine-specific ansatz. Optimized to reduce physical gates and SWAP operations, EnQode ensures all samples face consistent, low noise levels by standardizing circuit depth and composition. With over 90% fidelity in data mapping, EnQode enables robust, high-performance QML on noisy intermediate-scale quantum (NISQ) devices. Our open-source solution provides a scalable and efficient alternative for integrating classical data with quantum models.

Chandler Parkin, BYU

Title: Time Domain Simulations of Non-ideal Photonic Components with Simphony  

Abstract: Integrated photonic circuits excel in signal processing, sensing, and quantum information, but simulation tools are often cumbersome or inaccessible. We present the first open-source, Python-based software leveraging vector fitting for accurate time-domain simulations of non-ideal, compact models (including active components). Finally, we demonstrate a novel method for how this software could be used to evolve quantum Gaussian states in user defined circuits.

Ali Hamza Malik, Umass Amherst

Title: Verifying Quantum Protocol Interactions

Abstract: Quantum Key Distribution (QKD) promises provably secure communication by leveraging principles of quantum mechanics. However, while extensive research has focused on vulnerabilities in the quantum transmission phase, the classical communication phase remains an underexplored security frontier. In this work, we propose a formal verification framework for analyzing QKD protocols at the protocol level, ensuring comprehensive security evaluation across both quantum and classical components. Our approach employs symbolic modeling techniques to abstract quantum operations while preserving critical quantum properties, enabling scalable and automated security verification. By systematically analyzing end-to-end QKD implementations, we identify key design weaknesses and uncover previously overlooked vulnerabilities. Our findings emphasize the need for robust verification methodologies to enhance the reliability and security of quantum communication systems, paving the way for more resilient QKD deployments in practical scenarios. 

Tyler Stowell and Ben Fisher, BYU

Title: "Quantum Conference Key Agreement with a Photonic Integrated Circuit"

Abstract: Quantum Conference Key Agreement (QCKA) enables a group of users to simultaneously establish a secure shared key. However, implementations of QCKA protocols can be challenging due to the requirement for large multipartite entangled states. Here we overcome this barrier through the use of a passive linear photonic integrated circuit (PIC) dubbed the Green Machine which implements an eight mode Hadamard unitary transformation and allows for the generation of shared keys by interfering weak coherent pulses in a central relay. In addition to the first-ever fabrication and characterization of a PIC Green Machine, we report its performance in QCKA by calculating a secret key rate for five parties using a novel digital twin simulation. Under realistic conditions of noise and error, our PIC enables QCKA up to a range of 149 km between each party and a central relay.

Ankit Kumar Jha, UMass Amherst

Title : Post-Selection in Concatenated Bosonic and Discrete-Variable Error Correction Codes

Abstract : The Gottesman-Kitaev-Preskill (GKP) Codes are a promising candidate for continuous variable bosonic encoding of quantum information as they are robust against photon losses. These codes show improved performance when concatenated with Discrete-Variable Codes such as the [[7, 1, 3]] Steane Code. Errors in GKP qubits are in the form of shifts in quadrature which can be measured and corrected. These measured quadrature shifts can also be used to calculate the likelihood of successful error correction. This likelihood estimation technique can be used to throw away states which have a low probability of being correct which can greatly improve entanglement rate. This is called Post-Selection and has been shown to be beneficial for GKP only correction schemes. We show that combined with Discrete-Variable Codes, Post-Selection gives even better entanglement rates. Based on this observation, we propose two quantum network architectures for dense urban networks and long distance networks respectively and demonstrate the improvement in entanglement rate in these networks using post-selection.

Leonardo Bacciottini, UMass-Amherst

Title: How to Build a Packet-Switched Quantum Network

Abstract: Designing an operational architecture for the Quantum Internet is challenging in light of both fundamental limits imposed by physics laws and technological constraints. Here, we propose a method to abstract away most of the quantum-specific elements and formulate a best-effort quantum network architecture based on packet switching, akin to that of the classical Internet. This reframing provides an opportunity to exploit the many available and well-understood protocols within the Internet context. As an illustration, we tailor and adapt classical congestion control and active queue management protocols to quantum networks, employing an architecture wherein quantum end and intermediate nodes effectively regulate demand and resource utilization, respectively. Results show that these classical networking tools can be effective in managing quantum memory decoherence and maintaining end-to-end fidelity around a target value.