Qubit-Lab Logoqubit-lab.ch
Qubit Lab Logo

Qubit Lab

Quantum Computing. Demystified.

Clear insights for business leaders, practitioners, and quantum enthusiasts.

From executive awareness and quant education to practical use-case framing, rapid quantum prototyping, and PQC readiness, Qubit Lab helps organizations understand where quantum matters, where it does not, and how to prepare in a structured way.

ServicesExplore RQP SuiteExplore PQC Navigator

Quantum Computing. Straight Talk.

Qubit Lab makes quantum computing understandable, relevant, and actionable. It is designed for business leaders who need clarity on use cases, timing, and strategic implications, and for practitioners who want to understand the underlying concepts, algorithms, and code.

Through focused videos, practical examples, advisory-oriented content, and hands-on RQP tools, the platform connects quantum theory with real-world decision-making in finance, chemistry, and beyond.

Services

Qubit Lab supports organizations that want practical quantum guidance rather than abstract technology talk. The strongest current focus is on financial services, regulated environments, quantum education, use-case framing, rapid prototyping, and post-quantum cryptography readiness.

Quantum Advisory

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

Quantum Education

Executive briefings, management sessions, and expert training for teams that need clear and grounded understanding.

Rapid Quantum Prototyping

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

Explore ServicesView RQP SuiteStart the Conversation

Latest videos

Browse all
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.

STQFinance
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.

STQDeep DiveFinance
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.

FinanceDeep Dive
QAOA Search in Action
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.

ChemistryDeep Dive
Browse all videosBrowse STQBrowse StrategyBrowse PQCBrowse FinanceBrowse ChemistryBrowse IntroBrowse Deep Dive