Ionizing radiation events are a relevant limiting factor of superconducting qubit performance. While the coherence time (T₁) of the best superconducting qubits is not yet limited by ionizing radiation, recent studies have already pointed towards degradation of stability and performance caused by particle interactions within a quantum processor. In particular, qubit correlated errors caused by ionizing radiation are threatening to render useless the envisioned quantum error correction techniques. Moreover, ionizing radiation would start directly limiting T₁ around the 4 milliseconds mark, a near-future target.
Simultaneously, the high sensitivity of superconducting qubits to particle interactions can be exploited to build a new generation of particle detectors, enabling quantum sensing.
The first step to tackle the challenges posed by ionizing radiation is to fully understand how the energy released in the quantum processor deteriorates its performance. To do so, we build hybrid devices equipped with superconducting qubits and particle sensors used in low-temperature particle detectors. These new hybrid detectors can give us invaluable information regarding the disruption of the qubit coherence due to ionizing radiation interacting within the device.
At the same time, the high sensitivity to particle interactions of these hybrid devices can be exploited to build new detector prototypes which can find useful applications in other areas of physics, such as astroparticle physics.

The integration of 2D van der Waals (vdW) materials into superconducting circuits offers an exciting new approach to advancing quantum hardware. Their atomically clean interfaces, large and tunable kinetic inductance, and naturally layered heterostructures provide unique advantages for engineering low-loss Josephson elements, compact resonators, and scalable circuit architectures. These features open pathways to qubits with reduced footprint, suppressed parasitic coupling, and materials-level design flexibility that complements conventional thin-film quantum engineering.

In this talk, I will review recent progress in building superconducting qubits and circuit elements using vdW materials, outlining key design principles, fabrication challenges, and emerging opportunities. I will highlight our recent demonstration of all-vdW, merged-element transmon qubits that achieve high coherence (T₁ up to 100 μs) while leveraging the intrinsic advantages of layered superconductors. I will conclude with a perspective on the route toward extensible, wafer-scale quantum circuits constructed entirely from vdW superconductors, and the prospects this approach offers for next-generation quantum computing and sensing technologies.

[1] Nature Nanotechnology 14,120-125 (2019)

[2] Nature Materials 21, 398–403(2022)

[3] Nature 638, 99-105 (2025)

[4] arXiv:2511.08466 (2025)

Superconductor-semiconductor hybrid heterostructures show promise in enabling error-limited quantum computation through qubits with longer coherence times and topologically protected qubits. The development of hybrids began with the quest for improved material interfaces in the Al/InAs system, initially for topological superconductor research and subsequently for gate-tunable qubits. However, aluminium has limitations in terms of critical current, and many other superconductors remain under-explored. Therefore, searching for alternative material combinations, introducing novel superconductors and exploring innovative architectures is essential to overcoming the limitations of current hybrid devices.

In this study, we present our work on developing supercurrent-tunable nanowire Josephson junctions, using either parallel Al/InAs nanowires or an alternative superconductor, such as tin (Sn). Tin is known to have a higher critical temperature and superconducting gap than aluminium. However, it is an allotrope, meaning it can exist in multiple crystalline phases, only one of which is suitable for quantum bit technologies. Therefore, the crystalline phase of Sn must be controlled during epitaxy or deposition to favour the desired phase [1, 2], ensuring that interfaces remain undamaged during growth.

Building on these advances in material science, we demonstrate improved performance and robustness of the device. Both our strategies demonstrate significant improvement in critical current tunability. In the case of Sn/InAs nanowires, the devices additionally demonstrate strong resilience to magnetic fields [3]. Tunable and large critical currents, as well as resilience to magnetic fields, are essential properties for quantum devices. Finally, we will present measurements of Josephson parametric amplifiers [4] and gate-controlled qubits [5].

References:

[1] M. Pendharkar et al, Science (2021)

[2] A. H. Chen et al, Nanotechnology (2023)

[3] A. Sharma et al, Nano Letters (2025)

[4] R. Rousset et al, in prep. (2025)

[5] A. Purkayastha et al, arXiv:2508.04007v1 (2025)

The rapid development of artificial intelligence in the big data era has increased the demand for solving complex combinatorial optimization problems (COPs) such as vehicle routing problem (VRP), which are difficult to efficiently handle with conventional von-Neumann computing systems. Quantum computing, which utilizes quantum bits (qubits) based on the superposition of spin, shows potential for solving COPs. However, the requirement of cryogenic operating environments—necessary for noise elimination and accurate spin detection—remains a significant drawback. To address these challenges, probabilistic computing (P-computing) has recently been proposed as an alternative approach to emulate quantum supremacy even at room temperature.

Here, we showed probabilistic bits (P-bits) with a novel Ti/SiO_x/Ti stack, which is a fundamental building block for P-computing. The SiO_x layer typically exhibits reliable TS behavior, resulting in robust voltage oscillations. When a Ti scavenging layer was introduced at the interface, oxygen vacancies were provided to the SiO_x, causing oscillation to occur probabilistically. Through physical analysis and numerical calculations considering the charging and discharging process, we investigated the underlying mechanism of P-bit operation in the Ti/SiO_x/Ti stack. This results in a sigmoidal probability curve for ‘1’ over a wide range of input voltage. Finally, we verified that leveraging the developed SiO_x-based P-bit can significantly accelerate the algorithm for finding the optimal path in the vehicle routing problem through MATLAB simulation.

Probabilistic computing is a physics-based approach to addressing computational problems that are difficult to solve by conventional von Neumann computers, such as prime factorization (cryptography), MAX-CUT, or the Travelling Salesmen problem among others. A key requirement for p-computing is the implementation of fast, compact, and energy-efficient probabilistic bits (p-bits) that do not rely on pseudo-random number generators, as it is the case of stochastic systems based on CMOS technology. Among the different hardware proposals for p-bits, Magnetic Tunnel junctions (MTJs)1 have emerged as a strong candidate for realizing True Random Number Generators (TRNG). An MTJ is a nanoscale device consisting of two ferromagnetic electrodes separated by a dielectric barrier, which electrical resistance depends on the relative orientation of the magnetization of the ferromagnetic layers (Tunnel Magnetoresistance, TMR). In a technological point of view, MTJs have attracted interest as the fundamental block of Magnetic Random-Access Memories (MRAM), and its potential to integrate new device concepts such as neurons and synapses for Neuromorphic computing, microwave detectors (Spin Diodes)2 or Ising Spins in Ising Machines3.

In this talk, I will show how MTJs implement TNGs, and how we have implemented an stochastic computing scheme based on low energy barrier MTJs with tunable dwell time between states, i.e. Stochastic Computer4. Moreover, I will review an alternative p-bit design based on perpendicular MTJs that exploits the voltage-controlled magnetic anisotropy (VCMA)5 effect to generate the random state of a p-bit on demand, instead of use unstable MTJs. In this approach, the MTJ state is stable (i.e. have large energy barriers) in the absence of applied voltage, while VCMA-induced dynamics are used to generate random numbers in less than 10 ns/bit. A key advantage of VCMA-MTJs is that they do not require a bias current to tune the p-bit output, significantly reducing the impact of device variability across the chip as well as improving the device density. Finally, to demonstrate the feasibility of the proposed p-bits and the high quality of the generated random numbers, I will present a Probabilistic Computer based on VCMA-MTJs able to solve up to 40 bit integer factorization problems by a fully spintronic implementation of a p-bit, and alternatively, by enabling true random number generation at low cost for ultralow-power and compact p-computers implemented in complementary metal-oxide semiconductor chips.

Oscillatory  neural  networks  (ONNs),  which  encode  information  in  the  relative  phase  of  coupled oscillators, have emerged as a neuromorphic computing paradigm capable of addressing key limitations of conventional von Neumann architectures, such as limited parallelism and high energy consumption in computing large-scale tasks.[1-3] However, their scalability is challenged by the quadratic increase in coupling elements with network size and the requirement for programmable connectivity to support online learning.

To enable scalable and trainable ONN connectivity, resistive random-access memory (ReRAM) is introduced as the coupling element. ReRAM offers multilevel resistance states, low-power operation, and a compact 4F² footprint, making it an ideal candidate for programmable, dense interconnects. The ReRAM devices used in this work are bilayers whose active layers are composed of a conductive metal oxide (CMO) and a dielectric HfO_x, stacked between TiN electrodes.[4,5] After a one-time soft breakdown forming operation, a metallic filament composed of oxygen vacancies is created in the HfO_x layer. The resistive switching phenomenon is then governed by the redistribution of oxygen ions and vacancies in the CMO layer.[6] This mechanism provides the resistance tunability and stability required for coupling in ONNs.

A few key design constraints must be considered when integrating ReRAM as coupling elements in oscillator networks. Variations in oscillator voltages during computation may inadvertently alter the ReRAM state if voltage excursions exceed critical thresholds. In addition, the non-linear resistance response to applied voltage can lead to deviations in intended coupling strength, potentially degrading computing accuracy. These phenomena necessitate careful design strategies to ensure stable ONN functionality.[7] In this work, we establish a novel ONN architecture that uses ReRAM-based coupling elements, moving beyond traditional CMOS and passive coupling designs.  The approach spans materials science, device engineering, circuit design and integration, and includes application-level demonstrations—such as complex optimization and associative memory—on a functional hardware prototype for energy-efficient, neuromorphic computing.

Nonlinearity gives rise to the richness of mechanical systems, yet demonstrating nonlinearity that is relevant in the quantum regime has remained an open challenge. Overcoming this barrier is key to entering a new era of quantum nanomechanics. Nonlinear effects at the scale of zero-point motion are essential to unlock new regimes of quantum nanomechanics. We demonstrate that ultrastrong coupling (USC) between a nanotube mechanical oscillator and an electronic two-level system enables a mechanical Kerr nonlinearity at the zero-point motion scale. In the far-detuned dispersive USC regime, the large coupling yields a large mechanical anharmonicity while preserving the predominantly mechanical nature of the lowest energy states. This regime also realizes a cavity readout of the mechanical motion in a quantum non-demolition (QND) manner. The cavity readout is based on a purely quadratic optomechanical coupling, which can be tuned into the conventional linear interaction by electrostatic control.

The development of qubits has largely been guided by the requirements of fault-tolerant, gate-based quantum computing and, more recently, by topological quantum computing paradigms. These approaches impose exceptionally stringent constraints on materials quality, coherence times, and device uniformity, often requiring complex materials stacks, bespoke fabrication processes, and long technology maturation cycles. In contrast, quantum analog computing operates in a distinct regime in which scalability, reproducibility, and integration density take precedence over ultra-high coherence, enabling alternative materials and fabrication strategies.

This invited talk presents a materials-centric perspective on the realization of superconducting qubits for quantum analog computing, emphasizing the advantages of leveraging mature superconducting materials systems and CMOS-compatible microfabrication technologies. The use of well-established thin-film superconductors, conventional Josephson junction processes, and industrial process control enables high fabrication yield, improved parameter uniformity, and vertical integration across the hardware stack. These characteristics are essential for scaling quantum analog processors to large qubit counts while maintaining manageable complexity, cost, and development timelines.

Key materials challenges defining the performance envelope of quantum analog hardware will be discussed, including superconducting film uniformity, interface and dielectric losses, junction reproducibility, wiring density, and three-dimensional integration constraints. These challenges are contrasted with those encountered in fault-tolerant digital and topological quantum computing, illustrating how differing system-level requirements lead to fundamentally different materials bottlenecks and fabrication trade-offs. Rather than treating these paradigms as competing approaches, this perspective frames them as complementary stages within a broader superconducting quantum technology roadmap.

Superconducting quantum circuits are a versatile platform to study light-matter interaction and the Quantum Rabi model. The freedom in qubit and resonator designs and coupling engineering allows to study regimes of interaction beyond the bare frequencies of the system, entering the so-called ultrastrong coupling (USC) regime (0.1 < g/wr < 1) [1].

Non-perturbative ultrastrong couplings (0.3 < g/wr < 1) between a flux qubit and a resonator have been typically achieved using shared Josephson junctions. Recently, granular aluminum has been proposed as an alternative to reach ultrastrong couplings while keeping small persistent currents, and small qubit perimeters, which is advantageous for qubit coherence [2]. In this work, we present measurements of a flux qubit galvanically coupled to an LC oscillator by a shared wire of granular aluminum. The coupling is estimated to fall in the non-perturbative USC regime with g/wr ~0.3 and a persistent current below 40nA. This new approach opens the door to new designs with novel superinductors and the possibility to reach high coherence in ultrastrongly coupled flux qubit-resonator devices.