Equip your country for the quantum future and Connect universities & researchers globally.
QuantumGOB offers a unique combination of quantum computers, strategy, training, and ecosystem development, all integrated into products and services tailored to the needs of your country, region, and government.
We help you take the first steps toward building a quantum government, starting with a 5-qubit quantum computer and complete support in consulting, strategy, ecosystem development, and digital tools. QuantumGOB includes:
- Designing regional, national, and supranational quantum strategies
- Building industrial partnerships and international collaboration agreements
- Organizing high-level meetings and strategic events
- Coordinating ecosystem initiatives with public administrations & national entities
- Providing quantum hardware to foster talent development and real-world applications (SPARK system – 5 qubits)
- Deploying advanced quantum systems to enable industry-specific use cases (RADIANCE system – from 20 qubits)
- Offering cloud access to powerful quantum hardware for innovation development
McKinsey analysis reinforces this outlook, estimating that the IT load in Europe could rise from 10 GW today to approximately 35 GW by 2030, with data centres contributing to 15–25% of the net new electricity demand growth. This growth is concentrated in a limited number of countries: in Ireland, data centres already represent 18% of national demand, while in the Netherlands the share is approximately 7%. Such figures underscore the unsustainable trajectory of computing infrastructures, particularly if future quantum computers are not designed with energy efficiency as a central criterion.
The Energy Reversal: Cooling vs. Processing
In HPC, cooling typically accounts for 10%–30% of the system’s total power, as the classical chips generate intense heat. In current superconducting Quantum Computing systems, the cooling system alone consumes significantly more energy than the quantum chip itself, reversing the classical computing norm.
Theoretical Exponential Advantage
Quantum computation offers advantages over classical computation in terms of various computational resources; however, proving its energy-consumption advantage has been challenging due to the lack of a theoretical foundation linking the physical concept of energy with the computer-scientific notion of complexity for quantum computation. To bridge this gap, it introduced a general framework for studying the energy consumption of quantum and classical computation, based on a computational model conventionally used for studying query complexity in computational complexity theory.
To clarify how to estimate the energy consumption of classical computation for solving Simon’s problem to be compared with the results of the quantum experiments. The quantum experiment can demonstrate the energy-consumption advantage of quantum computation if the measured upper bound of the energy consumption for the quantum computation is smaller than an estimate for the classical computation. However, classical algorithms for solving the same problem cannot be realized due to the exponential run-time and the exponential energy consumption, and thus the energy consumption of the classical computation cannot be measured directly unlike that of quantum computation; after all, the main point of our analysis is that it is fundamentally infeasible for any classical algorithm to solve this problem, while the quantum algorithm can.
The Future of Efficiency
This exponential advantage means that if Quantum Computing cooling technology improves—or if scalable room-temperature quantum architectures emerge—quantum computers could eventually offer performance parity or superiority at a fraction of the energy cost of a classical HPC system. This potential for exponential energy efficiency, particularly for complex problems, is a primary driver for investment in quantum technology.
- Providing training and talent programs via the IQM Academy
- Licensing a fully customizable SaaS platform for quantum innovation and research ecosystems
- Delivering digital platform operations, support, and cloud services
- Developing strategies, leadership frameworks, and operational roadmaps for ecosystem digitalization
- Conducting training on academic-industry collaboration, innovation culture, leadership, and technology adoption
- Offering guidelines and “train-the-trainer” programs for managing hybrid and digital ecosystems
