Qilimanjaro Quantum Tech

Meet Andrea Pérez Martín, PhD student & Quantum Engineer at #Qilimanjaro! 💜 Andrea designs new devices, runs simulations, and heads down to the lab to measure them herself. In this video, she shares how she went from intern to quantum engineer with us. 🚀 #QuantumComputing #MeetTheTeam

⚛️ 𝐇𝐨𝐰 𝐝𝐨 𝐲𝐨𝐮 𝐦𝐨𝐯𝐞 𝐚 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐬𝐭𝐚𝐭𝐞 𝐚𝐜𝐫𝐨𝐬𝐬 𝐚 𝐜𝐡𝐢𝐩 𝐰𝐢𝐭𝐡 𝐨𝐧𝐥𝐲 𝐙𝐙 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐬? Transferring information between different parts of a quantum system with high fidelity is a hard problem with many candidate solutions, and none of them is ideal. Most rely on complex dynamics and fine control that do not apply to existing devices. We asked whether a protocol could be designed the other way around: starting from the hardware that exists today. 🔬 This work presents a 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐒𝐭𝐚𝐭𝐞 𝐓𝐫𝐚𝐧𝐬𝐟𝐞𝐫 (𝐐𝐒𝐓) 𝐩𝐫𝐨𝐭𝐨𝐜𝐨𝐥 that achieves fast and accurate transport of quantum states along spin chains, designed to work in state-of-the-art analog superconducting hardware. Our method is based on the continuous time evolution of the system under a time-independent Hamiltonian that encodes information as domain walls, allowing us to reproduce transport dynamics using exclusively nearest-neighbour Ising-like interactions. 📊 Numerical results show speeds well below the coherence times of fluxonium qubits, making this a strong candidate for state transfer schemes on analog devices. 🚀 As quantum computers grow in qubit count, moving information efficiently inside a chip becomes a prerequisite for running large-scale algorithms, and modular architectures turn chip-to-chip communication into the next challenge. Methods like ours are a step toward reliable state transfer on analog superconducting hardware. Congratulations to the authors! Oscar Michel Gonzalez, Matthias Werner, and Arnau Riera. 📄 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐩𝐚𝐩𝐞𝐫: https://lnkd.in/dVQmbJWW #QuantumComputing #AnalogQuantumComputing #QuantumStateTransfer #SuperconductingQubits #Qilimanjaro

⚛️ 𝐄𝐯𝐞𝐫𝐲 𝐧𝐞𝐰 𝐀𝐈 𝐦𝐨𝐝𝐞𝐥 𝐝𝐞𝐦𝐚𝐧𝐝𝐬 𝐜𝐨𝐦𝐩𝐮𝐭𝐞 𝐭𝐡𝐚𝐭 𝐝𝐨𝐞𝐬𝐧'𝐭 𝐞𝐱𝐢𝐬𝐭 𝐲𝐞𝐭, 𝐬𝐨 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐛𝐮𝐢𝐥𝐝 𝐛𝐢𝐠𝐠𝐞𝐫 𝐝𝐚𝐭𝐚 𝐜𝐞𝐧𝐭𝐞𝐫𝐬 𝐭𝐨 𝐫𝐮𝐧 𝐭𝐡𝐞𝐦. Then the next model needs even more power, more cooling, more chips. At some point, scaling one type of processor stops working. 🧠 Smart data centers stopped trying to do everything with one tool. They use GPUs for training, CPUs for serving, and custom chips for specific tasks, letting different processors handle different jobs in the same facility. 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐛𝐞𝐥𝐨𝐧𝐠𝐬 𝐢𝐧 𝐭𝐡𝐚𝐭 𝐬𝐚𝐦𝐞 𝐦𝐢𝐱, working alongside GPUs rather than replacing them. Integrating it now is what builds the synergy between modalities that industrially relevant problems will need. ⚛️ 𝐖𝐢𝐭𝐡 𝐒𝐩𝐞𝐐𝐭𝐫𝐮𝐦 𝐎𝐧-𝐏𝐫𝐞𝐦, we can install analog quantum computers, digital quantum computers, or both with classical systems under one software stack so users can route their jobs to whichever processor solves them best. That’s already happening. At the Barcelona Supercomputing Center (BSC), our latest work integrated both analog and digital quantum computers into the 𝐌𝐚𝐫𝐞𝐍𝐨𝐬𝐭𝐫𝐮𝐦 𝟓 supercomputer. Different processors working together, each handling the workloads they’re best suited for, instead of relying on a single computing architecture. #Qilimanjaro #QuantumComputing #AIInfrastructure #HPC #DataCenters

👀 People often think a quantum annealer and an analog quantum computer are the same thing. They're close relatives, but not the same. 🎯 𝐀𝐧 𝐚𝐧𝐧𝐞𝐚𝐥𝐞𝐫 𝐢𝐬 𝐛𝐮𝐢𝐥𝐭 𝐟𝐨𝐫 𝐨𝐧𝐞 𝐣𝐨𝐛: finding the best option among many choices, like planning the cheapest delivery route across a hundred cities. It can only use quantum annealing, an algorithm that works like a ball rolling downhill until it stops at the lowest point. That resting spot is the answer. Suited for optimization problems. 🔬 𝐀𝐧 𝐚𝐧𝐚𝐥𝐨𝐠 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐜𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐝𝐨𝐞𝐬 𝐭𝐡𝐚𝐭 𝐭𝐨𝐨, 𝐚𝐧𝐝 𝐦𝐨𝐫𝐞! An analog quantum computer is fully programmable and able to run a rich variety of algorithms. It can run Quantum AI workflows, such as Quantum Reservoirs, it can reproduce how molecules and materials behave, so scientists can study chemistry and physics that classical computers struggle with. And, of course, it can also run the quantum annealing algorithm for optimization problems. At Qilimanjaro Quantum Tech, we build this more flexible kind. Our chips use fluxonium qubits, which stay coherent longer, something these more complex problems need. #Qilimanjaro #QuantumComputing #AnalogQuantum #QuantumAnnealing

Why did we choose fluxonium qubits when most of the industry chose transmons? 💡 𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐭𝐡𝐞 𝐛𝐞𝐬𝐭 𝐪𝐮𝐛𝐢𝐭 𝐝𝐞𝐩𝐞𝐧𝐝𝐬 𝐨𝐧 𝐭𝐡𝐞 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧. Our CSO, Dr. Tim Duty, shares why fluxonium offers the flexibility needed for analog quantum computing, hybrid analog-digital systems, and long-term scalability. Swipe through to hear his perspective after 25 years working with superconducting qubits. 👀 #QuantumComputing #QuantumTechnology #SuperconductingQubits #Fluxonium #QuantumHardware #Innovation

Meet Dídac Torrent Martínez, Lab Manager and Mechanical Engineer at Qilimanjaro Quantum Tech! ⭐️ In this video, Dídac takes us behind the scenes of his work, sharing insights into the hands-on engineering that keeps our lab running and how he's contributing to our mission. 🚀 #QuantumComputing #TheFutureIsQuantum #MeetTheTeam #DeepTech

👀 𝐂𝐚𝐧 𝐲𝐨𝐮 𝐭𝐞𝐥𝐥 𝐰𝐡𝐞𝐭𝐡𝐞𝐫 𝐚 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐩𝐡𝐚𝐬𝐞 𝐭𝐫𝐚𝐧𝐬𝐢𝐭𝐢𝐨𝐧 𝐥𝐢𝐞𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐢𝐧𝐭𝐞𝐫𝐩𝐨𝐥𝐚𝐭𝐢𝐨𝐧 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐭𝐰𝐨 𝐇𝐚𝐦𝐢𝐥𝐭𝐨𝐧𝐢𝐚𝐧𝐬 𝐛𝐲 𝐨𝐧𝐥𝐲 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐚𝐭 𝐭𝐡𝐞𝐦?  The usual answer is no: you discretize the interpolation and compute the spectrum step by step, or use some other technique to track the interpolation path locally. 💡 𝐀 𝐧𝐞𝐰 𝐩𝐫𝐞𝐩𝐫𝐢𝐧𝐭 𝐛𝐲 𝐐𝐢𝐥𝐢𝐦𝐚𝐧𝐣𝐚𝐫𝐨 𝐬𝐡𝐨𝐰𝐬 𝐭𝐡𝐞𝐫𝐞 𝐢𝐬 𝐚𝐧𝐨𝐭𝐡𝐞𝐫 𝐰𝐚𝐲. Ana Palacios de Luis introduces an approximate joint symmetry analysis of just the initial and final Hamiltonians. By restricting to symmetries that can be efficiently identified and described, the method constructs an analytical approximation to the energy spectrum along the entire interpolation, i.e., a 𝐩𝐬𝐞𝐮𝐝𝐨𝐬𝐩𝐞𝐜𝐭𝐫𝐮𝐦, that retains the features that matter most: the signatures of gap closings, and whether it is only the gap with the first excited state that closes or if several other levels participate in the transition too. 🔬 Gap closings are the bottleneck of the adiabatic algorithm, precisely the class of algorithms our analog QPUs are built to run. Understanding the gap structure before running anything translates directly into the design of better algorithms and a better use of our hardware. 🔍 This framework provides a way of organising the information contained in a Hamiltonian interpolation that reveals physically meaningful structure and, ultimately, a new conceptual lens through which to analyse Hamiltonian interpolations and many-body quantum systems. 🎉 Congratulations to Ana and the team. 📄 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐩𝐫𝐞𝐩𝐫𝐢𝐧𝐭! https://lnkd.in/ePJDWwrc #QuantumComputing #QuantumAnnealing #AnalogQuantumComputing

🔬 𝐂𝐚𝐧 𝐰𝐞 𝐮𝐬𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐭𝐨 𝐫𝐞𝐬𝐡𝐚𝐩𝐞 𝐚 𝐪𝐮𝐚𝐧𝐭𝐮𝐦-𝐚𝐧𝐧𝐞𝐚𝐥𝐢𝐧𝐠 𝐥𝐚𝐧𝐝𝐬𝐜𝐚𝐩𝐞 𝐟𝐨𝐫 𝐛𝐞𝐭𝐭𝐞𝐫 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞? #QuantumAnnealing still has plenty of room to improve through better control strategies. Diagonal catalysts are one promising direction. Previous studies showed that they can help in specific settings, often when a useful reference configuration is already available. Our work asks a different question: can we design effective catalysts directly from the problem structure, without using information about the global solution? 𝐖𝐞 𝐚𝐝𝐝𝐫𝐞𝐬𝐬 𝐭𝐡𝐢𝐬 𝐢𝐧 𝐭𝐰𝐨 𝐩𝐚𝐫𝐭𝐬: 🧩 First, we derive a mathematical framework based on Hamming shells that describes how the energies of configurations are organized around the ground-state manifold. This gives static criteria for what a useful catalyst should achieve, such as deepening the average energy funnel and reducing the overlap between configurations at different Hamming distances. 💡 Second, we introduce a family of 𝐭𝐰𝐨-𝐛𝐨𝐝𝐲 𝐝𝐢𝐚𝐠𝐨𝐧𝐚𝐥 𝐜𝐚𝐭𝐚𝐥𝐲𝐬𝐭𝐬  constructed only from the signs and magnitudes of the problem couplings. They preserve the transverse-field annealing structure, are 𝐜𝐨𝐦𝐩𝐚𝐭𝐢𝐛𝐥𝐞 𝐰𝐢𝐭𝐡 𝐜𝐮𝐫𝐫𝐞𝐧𝐭 𝐬𝐮𝐩𝐞𝐫𝐜𝐨𝐧𝐝𝐮𝐜𝐭𝐢𝐧𝐠 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐚𝐧𝐧𝐞𝐚𝐥𝐢𝐧𝐠 𝐡𝐚𝐫𝐝𝐰𝐚𝐫𝐞, and improve the sampling of low-energy and near-solution configurations across several families of benchmark instances. 🛠️ We tested the catalysts on 200 random 3-regular instances, and on denser and fully-connected graphs. At a moderate sweep time, the probability of sampling a top-quality solution (within 5% of the ground-state energy) 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐚 𝐦𝐞𝐝𝐢𝐚𝐧 𝐨𝐟 +351%, 𝐰𝐢𝐭𝐡 99% 𝐨𝐟 𝐢𝐧𝐬𝐭𝐚𝐧𝐜𝐞𝐬 improved. These gains persisted on 4- and 5-regular graphs, as well as on the fully connected Sherrington-Kirkpatrick model. Our work thus opens a practical route to improving quantum annealing through problem-informed control, rather than relying on generic schedules alone. ✨ 📄 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐩𝐫𝐞𝐩𝐫𝐢𝐧𝐭:https://lnkd.in/ecfmc_hd Congratulations to all the authors! Andrés N. Cáliz, Carlos Ramon-Escandell, Finnley Paolella, Josep Bosch, Jan Nogué Gómez, Arnau Riera and Jordi Riu Vicente 💜 #QuantumComputing #Optimization #QuantumAlgorithms #Physics

We’re Hiring an Electronics and Instrumentation Hardware Engineer ⚙️ We are looking for a senior technical owner for the electronics and instrumentation layer of our quantum systems. This is a high-impact engineering position for someone who can define architectures, debug complex hardware systems, establish validation methods and raise the technical maturity of the team. We're looking for an autonomous, results-oriented profile who thrives in dynamic environments. We value the ability to make sound decisions, take ownership of one's own work, and adapt with agility to the company's shifting priorities. You do not need a quantum background. You will work alongside physicists and measurement specialists who operate the qubits; the physics will be explained to you. The qubit is, in the end, your most sensitive measuring instrument, but your job is to read what its behaviour tells you about the electrical chain and fix the root cause there. The electronics principles we need are universal. The challenge is applying rigorous electronics engineering discipline to a domain where that discipline is not yet fully established. We’re based in sunny Barcelona! 🌞🔗 𝐅𝐮𝐥𝐥 𝐣𝐨𝐛 𝐝𝐞𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧: https://lnkd.in/eYxaTRjG

𝐂𝐚𝐧 𝐚 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐚𝐧𝐧𝐞𝐚𝐥𝐞𝐫 𝐩𝐞𝐫𝐟𝐨𝐫𝐦 𝐚𝐥𝐥 𝐭𝐡𝐞 𝐭𝐚𝐬𝐤𝐬 𝐭𝐡𝐚𝐭 𝐚 𝐠𝐚𝐭𝐞-𝐛𝐚𝐬𝐞𝐝 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐜𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐜𝐚𝐧? For a long time, the answer was thought to be no. A new preprint from Qilimanjaro reopens the question and answers it: yes. Matthias Werner proves that the physics that most quantum annealers run on, the global transverse-field Ising model, is equivalent to the standard gate model of quantum computation 💡 𝐓𝐡𝐞 𝐤𝐞𝐲 𝐢𝐬 𝐦𝐨𝐭𝐢𝐨𝐧: when the global field is driven non-monotonically in time, the system can reproduce any quantum circuit, with only polynomial overhead. What stands out is how little it asks of the hardware: a single control line, and how much it asks of one thing: coherence. The whole scheme lives on coherent evolution: the longer the system stays coherent, the more of the algorithm you can run. ⚛️ This is why, as we always say, 𝐜𝐨𝐡𝐞𝐫𝐞𝐧𝐜𝐞 𝐢𝐬 𝐭𝐡𝐞 𝐦𝐞𝐭𝐫𝐢𝐜 𝐭𝐡𝐚𝐭 𝐦𝐚𝐭𝐭𝐞𝐫𝐬, and why we've long taken it as the north-star KPI of our devices. At Qilimanjaro, we build superconducting analog quantum computers: a native platform for precisely this class of algorithms, and many more! This work is a scientific (and patented!) milestone, and for us, an engineering roadmap. Congratulations to Matthias Werner and the team. 💜 📄 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐩𝐚𝐩𝐞𝐫: https://lnkd.in/eXYUsMUs #QuantumComputing #QuantumAnnealing #AnalogQuantumComputing