Qubit Lab

Quantum Computing for Financial Services.

Advisory, hands-on team enablement, and rapid quantum prototyping — with every quantum result benchmarked honestly against strong classical baselines.

qubit-lab.ch helps banks and other financial institutions understand where quantum computing matters, where it does not yet, and how to build practical capability in a structured way — from executive briefings and hands-on quantum coding enablement to prototype sprints with the RQP tool suite.

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Services

Practical quantum guidance rather than abstract technology talk. The strongest focus is on financial services and regulated environments: management clarity, hands-on quantum coding enablement, use-case framing, and rapid prototyping against classical benchmarks.

Quantum Advisory

Structured support for organizations exploring realistic quantum use cases, PoCs, decision paths, and internal next steps.

Quantum Capability Kickstart

Five interactive sessions for quant, risk, data science, innovation, and technology teams, focused on quantum fundamentals, coding, simple circuits, algorithm workflows, and practical experimentation.

from CHF 2'500 per participant (groups of 4–10)

Rapid Quantum Prototyping

Hands-on RQP tools for exploring quantum optimization, QML, and Quantum Monte Carlo workflows in a structured, benchmark-oriented way.

PQC Readiness

Practical support for post-quantum cryptography awareness, exposure visibility, stakeholder alignment, and readiness planning.

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Daniel Hug

Founder · MSc Physics ETH Zurich · MBA · PMP

Physicist and senior transformation professional with leadership experience across UBS, Credit Suisse, and SIX. Daniel supports financial institutions on quantum readiness and quantum risk, combining technical depth with a practical understanding of regulated change, governance, and implementation realities.

Connect on LinkedIn More about qubit-lab.ch

Selected work

3rd-eyes analytics AG

Wealthtech · Zurich

3rd-eyes analytics provides goal-based investment advice to financial institutions in Switzerland. Together we explored quantum approaches to core–satellite portfolio optimization — related to the goal-based, liability-aware variant used in their optimization engine — using QAOA and the RQP Suite. The joint work produced a quantum-inspired, classically executable alternative now being tested for their pipeline — and the same problem formulation can move to quantum hardware as it matures.

In collaboration with Felix Csajka, PhD, CFA — Head Investments, 3rd-eyes analytics AG

Global Swiss bank

Quant team briefing · 2026

Invited quantum computing briefing for a quant team: quantum fundamentals, algorithm workflows, and a realistic assessment of near-term applicability in finance — no hype, concrete enough for practitioners to act on.

“An excellent introduction — especially valuable because so few people in our field are familiar with the topic yet.”
— Quantitative Analyst (PhD), participant

Selected partners

qubit-lab.ch works with selected partners to support practical quantum computing enablement, enterprise technology perspectives, market access, and post-quantum cryptography readiness.

“Very happy to have qubit-lab.ch as our quantum partner — technically rigorous, refreshingly free of quantum hype, and reliable in front of clients.”
— Horn & Company

Insights

Browse all

Focused videos, practical examples, and hands-on quantum coding that connect quantum theory with real-world experimentation in finance, chemistry, and beyond.

Testing Quantum Computing in Finance: The RQP Suite

STQ#5

Released 17 Jun 2026

Testing Quantum Computing in Finance: The RQP Suite

Open on YouTube

Quantum computing is often discussed for finance use cases such as optimization, machine learning, and simulation. But before organizations can assess its relevance, they need a structured way to test quantum algorithms against classical baselines. This video introduces the Rapid Quantum Prototyping Suite by qubit-lab.ch, including modules for QAOA portfolio optimization, quantum machine learning with VQC and QSVM, and Quantum Monte Carlo experiments. The goal is practical experimentation, transparent benchmarking, and informed evaluation.

STQ Finance

QAOA Today: How Far Can NISQ Hardware Really Go? (as of April 2026)

STQ#4

Released 10 Apr 2026

QAOA Today: How Far Can NISQ Hardware Really Go? (as of April 2026)

Open on YouTube

QAOA is often presented as a promising approach for tackling complex optimization problems. But its real value depends on what today’s hardware can actually support. Current NISQ devices come with strict limitations: noise, limited connectivity, and shallow circuit depths. These are not minor details, they fundamentally shape what QAOA can and cannot achieve in practice. This video takes a grounded look at these constraints and translates them into realistic expectations. Not as a final verdict, but as a clearer picture of where we stand today and what remains out of reach.

STQ Deep Dive Finance

QAOA vs. Classical Search: How Quantum Optimization Redirects the Search

FINANCE#20

Released 02 Apr 2026

QAOA vs. Classical Search: How Quantum Optimization Redirects the Search

Open on YouTube

This video visually compares a classical sequential search with quantum optimization using QAOA. While the classical approach evaluates candidates one by one, QAOA reshapes probabilities across the full solution space to guide the search toward better outcomes. The side-by-side visualization shows how both approaches behave and why quantum optimization differs fundamentally from classical candidate-by-candidate evaluation. The QAOA search shown here is based on a real QAOA run, not a mockup.

Finance Deep Dive

STQ#3

Released 02 Apr 2026

QAOA Search in Action

Open on YouTube

This short visually compares a classical sequential search with quantum optimization using QAOA. (see the full video in the finance section)

STQ

QCBM for Quantum Finance: Credit Spread Copulas and Tail Risk

FINANCE#19

Released 23 Mar 2026

QCBM for Quantum Finance: Credit Spread Copulas and Tail Risk

Open on YouTube

This video presents a structured quantum-finance use case built around copula-based dependence modeling and quantum scenario generation for credit spread tail risk. It explains how empirical credit spread data can be transformed into a joint dependence distribution, why tail regions are difficult to model with sparse classical observations alone, and how a Quantum Circuit Born Machine can be used to learn and sample from that distribution. The discussion covers the intuition behind empirical, Gaussian, and t-copulas, the role of tail dependence in credit risk, and the practical logic of discretizing the joint space before training a quantum generative model. It also positions the workflow in the broader context of Quantum GenAI, highlighting how quantum models may eventually support scenario generation for rare but relevant financial stress events. The goal is to provide a technically grounded but accessible walkthrough of a realistic quantum-finance modeling pipeline.

Finance

Quantum Chemistry 2: Hamiltonian Simulation Algorithms (VQE, ADAPT-VQE, QPE, Trotterization, Qubitization)

CHEMISTRY#18

Released 06 Mar 2026

Quantum Chemistry 2: Hamiltonian Simulation Algorithms (VQE, ADAPT-VQE, QPE, Trotterization, Qubitization)

Open on YouTube

The video builds on the first chemistry introduction and compares the main quantum algorithm choices for estimating molecular ground-state energies in a structured, step-by-step overview. It explains which approaches are relevant on current NISQ hardware, which belong to the fault-tolerant era, and why that distinction matters when assessing realistic timelines for quantum advantage in chemistry. Coverage includes VQE and ADAPT-VQE as near-term hybrid methods, as well as Quantum Phase Estimation with trotterization and with qubitization, including the key tradeoffs in circuit depth, precision, measurement effort, and asymptotic scaling. The goal is to provide a clear framework for understanding what is feasible now and what may become important later. This video was created for an audience seeking a technically informed comparison.

Chemistry Deep Dive

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