From Problem-Structured QAOA to Problem-Agnostic Variational MaxCut Solvers: Representation, Redundancy, and Optimization Landscapes

Time Series Anomaly Detection with Quantum Variational Methods and Set Covering

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Published: July 01, 2026

Our contribution on time-series anomaly detection at ICASSP 2026 (see this previous post) has been published here. The main focus of this paper has been to imporve upon our previous work on time-series prediction using QAOA and set covering strategie. More materials are available in these blog posts here and here. Read more

Papers related to the 2026 IEEE International Symposium on Circuits and Systems

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Published: June 30, 2026

We recently presented two contributions at the 2026 IEEE International Symposium on Circuits and Systems (ISCAS) in Shanghai. These contributions are a natural continuation of our works about time-space trade-offs in quantum cryptosystems (I’ve talked about this research topic in a couple of blog posts, se e.g. here). In this case we focused on two complementary aspects of the quantum version of the “Hellman construction” proposed last year at the same conference in London (cf., this post and this paper)

• A paper about a unified framework for cryptographic search based on quantum walks and Grover’s algorithm
• A paper about the impossibility of having multiplicative resource scaling in cryptographic search under the previous unified model.

Enhancing QAOA Ansatz via Multi-Parameterized Layer and Blockwise Optimization

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Published: May 06, 2026

The contribution about QAOA in the conference ICASSP 2026 (see this previous post) has been published here. I’ve also updated the blog, with a brief discussion about the main ideas behind the paper. In particular, in this paper we focus on multi-parameterized layers and advanced parameters’ update, in particular on the effect that an extra layer at the end of a standard QAOA circuit has, and on possible (blockwise) optimizations of the parameters of the extended circuit, including ablation studies. Concretely, applied to the MaxCut problem across diverse graph families, the proposed architecture achieves, with an order of magnitude smaller circuit depth, approximation ratios comparable to QAOA, using a single cost–mixer layer, thus reducing gate counts by up to fivefold. Moreover, ablation studies prove that blockwise fine-tuning is crucial to deliver higher-quality solutions at shallower depth, offering a practical, quantum hardware-efficient alternative for signal processing applications. Most of the code is an adaptation of this repository. Read more

Papers related to the 2026 IEEE International Conference on Acoustics, Speech, and Signal Processing

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Published: March 12, 2026

I’m happy to announce that we will share two contributions at the conference ICASSP 2026. The first contribution is a natural extension and enhancement of the Hybrid quantum-classical approach for anomaly detection in one-dimensional time series discussed here. The second contribution, instead, is focused on the QAOA and proposes a new variant of this quantum optimization algorithm where the standard QAOA ansatz is enhanced via a blockwise optimization strategy of its parameters and with the addition of a multi-parameterized layer before the measurements. Further details about this second contribution will be given in a subsequent announcement (I still have to update the blog!). If you are in Barcelona in the period 4-8 may we have our presentations already scheduled (see here and here), feel free to say hi to my colleagues! Read more