The Quantum Computing Podcast with Fexingo: Qubits, Quantum Hardware, and Future Computing

Episode 62 of The Quantum Computing Podcast with Fexingo dives into the memory bottleneck facing quantum computers. Lucas and Luna explore why today's classical RAM can't keep up with qubit error correction, and how a startup called Qunnect is building a quantum memory system using diamond defects. They break down the specific challenge: logical qubits require thousands of physical qubits, and each error-correction cycle needs to store and retrieve intermediate results faster than decoherence destroys them. The episode walks through the concept of a quantum cache, the physics of nitrogen-vacancy centers in diamond, and the trade-offs between optical and microwave readout. A concrete look at one of quantum computing's most overlooked hardware problems.

#QuantumComputing #QuantumMemory #Technology #Qubits #ErrorCorrection #DiamondDefects #Qunnect #NitrogenVacancy #QuantumCache #Decoherence #LogicalQubits #QuantumHardware #Cryogenics #RAM #QuantumComputingPodcast #FexingoBusiness #BusinessPodcast #Podcast

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Episode 61 of The Quantum Computing Podcast with Fexingo dives into the Haber-Bosch process, the 100-year-old industrial method for making ammonia fertilizer that consumes 2% of global energy and emits 450 million tons of CO2 annually. Lucas and Luna explore how quantum computers could simulate nitrogen fixation at the molecular level, potentially enabling a room-temperature, low-pressure alternative. The episode focuses on the specific challenge of modeling the iron catalyst's active site—a problem too complex for classical computers—and how companies like D-Wave and QC Ware are beginning to prototype quantum simulations. No hype, just a concrete look at a single industrial bottleneck where quantum advantage could have massive climate impact. The hosts also briefly discuss why the show stays ad-free and how listener support helps.

#QuantumComputing #HaberBosch #Ammonia #Fertilizer #Emissions #ClimateTech #NitrogenFixation #CatalystSimulation #IndustrialChemistry #DQave #QCWare #QuantumAdvantage #Technology #FexingoBusiness #BusinessPodcast #LucasAndLuna #QuantumSoftware #GreenChemistry

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Lucas and Luna dig into one of the quietest bottlenecks in quantum computing: memory that works at millikelvin temperatures. Classical DRAM freezes solid below about 40 kelvin. But today's superconducting qubits operate inside dilution refrigerators at roughly 10 to 15 millikelvin — a thousand times colder. Every control pulse and every measurement result currently has to be heat-carrying electrical signals traveling up and down cryostat wiring. Researchers at imec and MIT Lincoln Lab are testing cryogenic CMOS memory arrays designed to function below 4 kelvin. Lucas walks through the numbers: a 16-kilobyte cryo-CMOS test chip that draws under 1 milliwatt and can serve a 100-qubit processor without violating the system's thermal budget. Luna asks whether this is a sideline or a gating factor — and the answer is that without on-chip memory, scaling beyond a few hundred qubits becomes physically impossible. The hosts also touch on why this matters for the broader quantum timeline and how classical semiconductor fabs can adapt existing processes for cryo conditions.

#QuantumComputing #CryogenicMemory #CryoCMOS #QubitScaling #SuperconductingQubits #DilutionRefrigerator #imec #MITLincolnLab #ThermalBudget #Millikelvin #MemoryBottleneck #QuantumHardware #ScalingChallenge #Technology #FexingoBusiness #BusinessPodcast #TechPodcast #QuantumPodcast

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Supply chains are notoriously chaotic—disruptions ripple across continents, and traditional optimization breaks down under real-world constraints. In this episode, Lucas and Luna explore how quantum computing is beginning to tackle supply chain complexity, focusing on a 2025 pilot by Volkswagen that used a hybrid quantum-classical solver to route spare parts across European warehouses. They unpack why classical algorithms struggle with multi-echelon inventory problems, how quantum annealers and variational circuits offer a different approach, and what the current hardware limitations mean for deployment today. The conversation covers specific benchmarks: a 127-qubit IBM processor versus a commercial solver, cost savings in the range of 3–5 percent for logistics networks, and why the biggest wins may come from combining quantum with classical heuristics rather than going pure quantum. Listeners will come away understanding the near-term promise and the hard problems that remain—no hype, just the actual state of play as of mid-2026.

#QuantumComputing #SupplyChain #Optimization #Volkswagen #Logistics #HybridQuantumClassical #QuantumAnnealing #IBM #Industry #NearTermQuantum #SupplyChainComplexity #FexingoBusiness #BusinessPodcast #Technology #Podcast #Fexingo #LucasAndLuna #QuantumPodcast

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Episode 58 of The Quantum Computing Podcast shifts focus from qubit design to the brutal economics of fabrication. Lucas and Luna explore why the industry's biggest bottleneck in 2026 isn't error correction — it's chip yield. Drawing on real numbers from Intel's tunnel-fab and IBM's Heron processor, they explain how manufacturing defects that barely matter in classical chips can kill entire quantum processors. The hosts discuss how the industry is borrowing 'known good die' strategies from classical chipmaking, the role of cryogenic wafer probing, and why the first fault-tolerant quantum computers may be assembled from a handful of working modules harvested from dozens of flawed wafers.

#QuantumComputing #ChipYield #ManufacturingDefects #QuantumHardware #FaultTolerance #Intel #IBM #HeronProcessor #KnownGoodDie #CryogenicProbing #QubitFabrication #ModularQuantum #Technology #Semiconductors #QuantumEconomics #Podcast #FexingoBusiness #BusinessPodcast

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Lucas and Luna dive into why scaling quantum computers to useful sizes demands a shift from monolithic chips to modular, networked architectures. They discuss the physical limits of packing more qubits onto a single chip, the role of photonic interconnects, and the concrete challenges of linking separate quantum modules without destroying coherence. The episode focuses on recent progress at companies like IonQ and QuTech on building modular traps and mid-circuit interconnect links. Lucas explains why module-to-module error rates must drop below 1 percent for the approach to work, and why today's best demonstrations are still about 10 times too noisy. Luna questions whether modularity adds too much latency for error correction to keep up. The hosts also touch on a listener-supported model that keeps the show ad-free.

#QuantumComputing #ModularArchitecture #IonQ #QuTech #PhotonicInterconnects #QubitScaling #QuantumHardware #FaultTolerance #QuantumNetworking #TrappedIons #Technology #FexingoBusiness #BusinessPodcast #QuantumFuture #CryogenicEngineering #LogicalQubits #MidCircuitMeasurement #CoherenceTime

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Episode 56 of The Quantum Computing Podcast dives into quantum compilation — the unsung layer between a programmer's code and a machine's microwave pulses. Lucas and Luna discuss why today's compilers lose 80% of qubit coherence time just scheduling operations, and how a team at the University of Chicago's new method called 'temporal slicing' cuts that overhead in half. They walk through a concrete example: a 50-qubit simulation of a lithium-sulfur battery molecule that would take a classical computer 12,000 years. With temporal slicing, the same simulation runs in 47 hours on a trapped-ion machine. The hosts also explore why hardware-native gate sets force compilers into suboptimal paths, and how the race between superconducting, trapped-ion, and photonic hardware means compilers must be hardware-agnostic. No hype, just the real bottleneck that'll determine whether quantum computing delivers on its timeline.

#QuantumCompilation #QubitCoherence #TemporalSlicing #UniversityOfChicago #LithiumSulfurBattery #TrappedIon #SuperconductingQubits #PhotonicQuantum #GateSet #QuantumAlgorithms #Simulation #CompilerDesign #QuantumSoftware #Technology #FexingoBusiness #BusinessPodcast #QuantumComputing #HardwareAbstraction

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In this episode of The Quantum Computing Podcast with Fexingo, Lucas and Luna explore how quantum sensors — not quantum computers — are already delivering real-world value by mapping underground resources. They dive into a specific case: a 2025 pilot project in Canada where a quantum gravity gradiometer located a deep lithium deposit more accurately than classical methods. The hosts explain how quantum sensing leverages superposition and entanglement to measure gravitational fields with unprecedented precision, and why this technology is leapfrogging full-scale quantum computing in commercial deployment. They discuss the business implications for mining, oil and gas, and geothermal energy companies, and the startup landscape including companies like Q-CTRL and Xanadu that are commercializing these sensors. The episode also touches on the technology's limitations, including current depth constraints and the need for cryogenic cooling, and what the next five years might hold for the sector. A focused, concrete look at a technology that is quietly changing resource exploration today.

#QuantumSensors #QuantumGravityGradiometer #LithiumMining #ResourceExploration #QuantumTechnology #MiningTech #GeothermalEnergy #Q-CTRL #Xanadu #QuantumComputing #Superposition #Entanglement #Cryogenics #CanadaMining #DeepDeposits #BusinessPodcast #FexingoBusiness #Technology

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Episode 54 of The Quantum Computing Podcast explores how quantum algorithms are beginning to tackle one of the most frustrating urban problems: traffic congestion. Lucas and Luna examine a pilot project in a mid-sized European city where a quantum solver re-routes emergency vehicles and buses in real time. They unpack the specific combinatorial optimization challenge — the 'vehicle routing problem' — and explain why classical computers struggle beyond a few hundred nodes. The episode also discusses the hybrid quantum-classical approach used, the role of dedicated hardware from a startup called Qplanner, and what this means for smart city infrastructure. No hype, just a concrete look at where quantum optimization stands today, June 2026, and how it might scale beyond pilot projects.

#QuantumComputing #TrafficOptimization #VehicleRoutingProblem #SmartCities #Qplanner #HybridQuantum #CombinatorialOptimization #CityPlanning #Logistics #QuantumAlgorithms #Startup #PilotProject #RealWorldQuantum #FexingoBusiness #BusinessPodcast #Technology #QuantumTech #UrbanMobility

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In episode 53 of The Quantum Computing Podcast with Fexingo, Lucas and Luna explore a breakthrough that's quietly shifting quantum computing from theoretical promise toward practical reality: error correction that actually works at scale. We dive into Google's recent demonstration of a logical qubit with error rates below the surface-code threshold—a milestone that many researchers thought was years away. We explain what a logical qubit is, why error correction has been the field's 'final boss,' and how Google's team used a 17-qubit superconducting processor to encode one reliable qubit. Lucas breaks down the math: physical qubit error rates near 0.1 percent, logical error rates around 0.03 percent. Luna questions whether this can scale to the thousands of logical qubits needed for useful algorithms. We also look at parallel work from IBM and Quantinuum on alternative codes. If you've been waiting for quantum computing to deliver on its hype, this episode explains why error correction might finally be the unlock.

#QuantumComputing #ErrorCorrection #GoogleQuantum #LogicalQubit #SurfaceCode #IBMQuantum #Quantinuum #Qubits #QuantumTechnology #Technology #FexingoBusiness #BusinessPodcast #Podcast #Fexingo #LucasAndLuna #QuantumBreakthrough #SuperconductingQubits #QuantumScaling

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