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Key Takeaways

• The core bottleneck in simulation is mathematical models—not hardware

• Quantum-inspired algorithms are already delivering ~10× improvements on classical systems

• Future gains (~1000×) depend on both algorithmic evolution and hardware maturity

• India’s challenge is not talent, but risk appetite, execution, and ecosystem alignment

• Adoption requires integration with existing tools, not disruption of workflows

‍

Rethinking the Quantum Narrative

Sudhi Sachdev:
Quantum computing is often seen as a hardware race. Do you agree with that framing?

‍

Aditya Singh:
That’s the common perception—but it misses the real issue. The limitation today is the mathematics used in simulations. These models haven’t fundamentally changed in decades. Hardware has improved, but it’s only compensating for inefficient methods.

‍

From Hardware Scaling to Mathematical Innovation

Sudhi Sachdev:
What led BQP to focus on changing the math instead of waiting for quantum hardware?

‍

Aditya Singh:
We saw real problems across industries—simulations taking months, increasing complexity, and no scalable solution. Instead of relying on more compute, we rebuilt the algorithms from scratch using quantum-inspired approaches that work on current systems.

‍

Real-World Impact: Speed and Solution Quality

Sudhi Sachdev:
What kind of improvements are you seeing in practice?

‍

Aditya Singh:
It depends on the use case, but we’ve seen problems go from 12 hours to a few minutes—with the same accuracy. More importantly, we don’t just find one solution. We explore the full design space and provide multiple viable outcomes.

‍

Why Classical Systems Fall Short

Sudhi Sachdev:
Where do traditional approaches struggle the most?

‍

Aditya Singh:
As complexity increases, classical methods require exponentially more hardware. They also tend to get stuck in local optima. That limits both speed and the quality of decisions derived from simulations.

‍

India’s Quantum Opportunity—and Gaps

Sudhi Sachdev:
India has strong talent. What’s holding progress back?

‍

Aditya Singh:
Talent isn’t the issue. The gaps are in risk-taking, collaboration, and execution. We don’t see enough consortium-driven innovation, and adoption is slow because organizations wait for proven results instead of experimenting early.

‍

Bridging the Adoption Barrier

Sudhi Sachdev:
How do you address resistance from industries using legacy systems?

‍

Aditya Singh:
You don’t force change—you integrate. We’ve built our solutions to work with existing tools like MATLAB. Engineers don’t need to relearn systems. That makes experimentation much easier.

‍

The Transition to Quantum Computing

Sudhi Sachdev:
How should organizations approach quantum adoption today?

‍

Aditya Singh:
It’s a gradual transition—from classical to quantum-inspired, then hybrid, and eventually full quantum. If you wait for mature hardware, you’ll already be behind. The advantage comes from starting now.

‍

Final Perspective

Quantum computing is no longer just theoretical. The algorithms, infrastructure, and talent are already in place. The key differentiator is who starts experimenting first.

→ Listen to the Episode

‍

Guest: Abhishek Chopra, Founder & CEO, BosonQ Psi (BQP)

Podcast: Tech Scenes Unplugged with Jeff James Martin

BQP’s Founder discusses how BQPhy® uses quantum-inspired algorithms to accelerate simulations by over 10x in aerospace and defense. The conversation spans from the science behind hybrid computing to building scalable software from quantum physics.

‍→ Listen Now

‍

Podcast: Aerospace & Defense Technology

This episode explores how quantum-accelerated simulation is redefining digital twins — fromfaster design cycles to real-time mission analytics. Learn how BQP’s collaboration with the U.S.Air Force Research Laboratory (AFRL) is advancing mission-critical modeling through quantum-inspired solvers that bridge today’s HPC systems with tomorrow’s quantum-readyinfrastructure.

→ Listen Now

Podcast: ASV Ventures Tech Series

Abhishek Chopra reflects on BQP’s journey — from a computational challenge at RPI to pioneering quantum-inspired engineering. This conversation touches on startup lessons,algorithmic breakthroughs, and the human side of innovation — where spirituality, physics, andpurpose converge to shape a new era of intelligent simulation.

→ Learn more

In this episode of Coffee with a Founder, Abhishek Chopra shares how outdated mathematics —not compute power — is slowing aerospace innovation. He explains how BQP uses quantum-inspired algorithms to modernize simulation workflows, reduce aircraft design time, and unlockscalable engineering performance.

‍‍

→ Listen Now

‍

Key Takeaways

• Aerospace simulation bottlenecks are mathematical, not computational

• Quantum-inspired algorithms deliver value today

• Hybrid classical-quantum systems are the future

• Founder success depends on coachability and balance

‍

Beck Bamberger:

Welcome to Coffee with a Founder. Today we’re joined by Abhishek Chopra, founder and CEOof BQP. You’re building next-generation solutions to solve computational challenges in aerospace and defense using quantum-inspired algorithms. What made you leave academiaand start this company?

‍

Abhishek Chopra:

Thank you for having me. I’m an aerospace engineer and computational scientist by training. During graduate school, I developed large-scale turbulence simulations. One simulation took sixmonths on 250,000 computers.

‍

Industry typically runs thousands of simulations per component. When you multiply that across millions of components, it becomes unsustainable.

‍

That’s when I started asking: how can we make this faster and more practical?

‍

The Compute vs Math Problem

‍

Beck Bamberger:

Is the issue simply that we need more powerful computers?

‍

Abhishek Chopra:

No. That’s the surprising part.

We already have immense compute power. The problem is that the mathematical foundations of these tools haven’t changed in forty years.

Even when I migrated codes from CPUs to GPUs, including work with national labs and NVIDIA, we saw only incremental gains. The algorithms themselves were outdated.

So the bottleneck is math — not hardware.

‍

Quantum-Inspired Approach

‍

Beck Bamberger:

What does quantum-inspired mean in this context?

‍

Abhishek Chopra:

Quantum-inspired algorithms use mathematical frameworks from quantum information science but run on classical hardware like CPUs and GPUs.

Quantum computers will eventually become part of data centers. But they will sit alongside CPUs and GPUs, not replace them.

Today, we can extract significantly more performance from existing infrastructure by improving the mathematics.

‍

Real-World Impact

‍

Beck Bamberger:

Can you share an example?

‍

Abhishek Chopra:

We worked with an aerospace company to redesign aircraft wings. By improving simulation efficiency, they were able to reduce weight, cut fuel costs, and accelerate design cycles.

This is what better math enables.

‍

Founder Growth and Mentorship

‍

Beck Bamberger:

What has been your biggest unlock as a founder?

‍

Abhishek Chopra:

penness and coachability.

Coming from academia, it’s easy to carry pride in science. But building a company requires humility. It requires being open to new business models, pricing strategies, and partnerships.

A mentor once told me: always walk in the path of opening more doors. When making decisions, choose the path that expands opportunity.

That principle still guides me

‍

Work-Life Balance

‍

Beck Bamberger:

How do you sustain this long-term?

‍

Abhishek Chopra:

Entrepreneurship is a marathon. Maintaining health, relationships, and balance is critical.

Professional success matters, but personal well-being sustains the journey.


→ Listen Now

Podcast: The David Daily Show

Quantum computing is transitioning from theory to real aerospace and defense workflows. Inthis episode, Abhishek discusses how quantum-inspired simulations are already solvingcomplex flight challenges, the importance of partnerships like NVIDIA, and why buildingquantum-ready infrastructure today is critical for long-term competitiveness.

→ Listen Now

‍

Key Takeaways

• Quantum-inspired computing already delivers real engineering value

• Aerospace simulation is a leading application domain

• GPU infrastructure is enabling near-term scalability

• Quantum readiness depends on system-level preparation, not just hardware

‍

David Goecke:

Quantum computing is often discussed as a future technology. From your perspective, where are we seeing real-world applications today?

‍

Abhishek Chopra:

We are already seeing value in engineering workflows, particularly in simulation. Instead of waiting for large-scale quantum hardware, we use quantum-inspired algorithms that run on classical systems to solve complex optimization and physics problems.

‍

Quantum in Aerospace Workflows

David Goecke:

What makes aerospace a strong early application area?

‍

Abhishek Chopra:

Aerospace simulations involve extremely complex physics and large datasets. Traditional approaches require significant simplifications. Quantum-inspired methods help reduce computational bottlenecks and allow higher-fidelity modeling.

‍

Infrastructure and GPU Ecosystems

David Goecke:

How important is the role of modern computing infrastructure?

‍

Abhishek Chopra:

It is critical. Advances in GPU computing have enabled us to scale these algorithms effectively. By leveraging high-performance computing systems, we can deliver practical solutions today while building pathways toward future quantum integration.

‍

Preparing for the Quantum Transition

‍

David Goecke:

What should organizations focus on now?

‍

Abhishek Chopra:

They should focus on infrastructure readiness, workforce capabilities, and scalable computational workflows. The transition to quantum computing will be gradual, andpreparation today determines long-term advantage.

‍

→ Listen to the Episode

Key Takeaways

• The core bottleneck in simulation is mathematical models—not hardware

• Quantum-inspired algorithms are already delivering ~10× improvements on classical systems

• Future gains (~1000×) depend on both algorithmic evolution and hardware maturity

• India’s challenge is not talent, but risk appetite, execution, and ecosystem alignment

• Adoption requires integration with existing tools, not disruption of workflows

‍

Rethinking the Quantum Narrative

Sudhi Sachdev:
Quantum computing is often seen as a hardware race. Do you agree with that framing?

‍

Aditya Singh:
That’s the common perception—but it misses the real issue. The limitation today is the mathematics used in simulations. These models haven’t fundamentally changed in decades. Hardware has improved, but it’s only compensating for inefficient methods.

‍

From Hardware Scaling to Mathematical Innovation

Sudhi Sachdev:
What led BQP to focus on changing the math instead of waiting for quantum hardware?

‍

Aditya Singh:
We saw real problems across industries—simulations taking months, increasing complexity, and no scalable solution. Instead of relying on more compute, we rebuilt the algorithms from scratch using quantum-inspired approaches that work on current systems.

‍

Real-World Impact: Speed and Solution Quality

Sudhi Sachdev:
What kind of improvements are you seeing in practice?

‍

Aditya Singh:
It depends on the use case, but we’ve seen problems go from 12 hours to a few minutes—with the same accuracy. More importantly, we don’t just find one solution. We explore the full design space and provide multiple viable outcomes.

‍

Why Classical Systems Fall Short

Sudhi Sachdev:
Where do traditional approaches struggle the most?

‍

Aditya Singh:
As complexity increases, classical methods require exponentially more hardware. They also tend to get stuck in local optima. That limits both speed and the quality of decisions derived from simulations.

‍

India’s Quantum Opportunity—and Gaps

Sudhi Sachdev:
India has strong talent. What’s holding progress back?

‍

Aditya Singh:
Talent isn’t the issue. The gaps are in risk-taking, collaboration, and execution. We don’t see enough consortium-driven innovation, and adoption is slow because organizations wait for proven results instead of experimenting early.

‍

Bridging the Adoption Barrier

Sudhi Sachdev:
How do you address resistance from industries using legacy systems?

‍

Aditya Singh:
You don’t force change—you integrate. We’ve built our solutions to work with existing tools like MATLAB. Engineers don’t need to relearn systems. That makes experimentation much easier.

‍

The Transition to Quantum Computing

Sudhi Sachdev:
How should organizations approach quantum adoption today?

‍

Aditya Singh:
It’s a gradual transition—from classical to quantum-inspired, then hybrid, and eventually full quantum. If you wait for mature hardware, you’ll already be behind. The advantage comes from starting now.

‍

Final Perspective

Quantum computing is no longer just theoretical. The algorithms, infrastructure, and talent are already in place. The key differentiator is who starts experimenting first.

→ Listen to the Episode

‍

Guest: Abhishek Chopra, Founder & CEO, BosonQ Psi (BQP)

Podcast: Tech Scenes Unplugged with Jeff James Martin

BQP’s Founder discusses how BQPhy® uses quantum-inspired algorithms to accelerate simulations by over 10x in aerospace and defense. The conversation spans from the science behind hybrid computing to building scalable software from quantum physics.

‍→ Listen Now

‍

Podcast: Aerospace & Defense Technology

This episode explores how quantum-accelerated simulation is redefining digital twins — fromfaster design cycles to real-time mission analytics. Learn how BQP’s collaboration with the U.S.Air Force Research Laboratory (AFRL) is advancing mission-critical modeling through quantum-inspired solvers that bridge today’s HPC systems with tomorrow’s quantum-readyinfrastructure.

→ Listen Now

Podcast: ASV Ventures Tech Series

Abhishek Chopra reflects on BQP’s journey — from a computational challenge at RPI to pioneering quantum-inspired engineering. This conversation touches on startup lessons,algorithmic breakthroughs, and the human side of innovation — where spirituality, physics, andpurpose converge to shape a new era of intelligent simulation.

→ Learn more

In this episode of Coffee with a Founder, Abhishek Chopra shares how outdated mathematics —not compute power — is slowing aerospace innovation. He explains how BQP uses quantum-inspired algorithms to modernize simulation workflows, reduce aircraft design time, and unlockscalable engineering performance.

‍‍

→ Listen Now

‍

Key Takeaways

• Aerospace simulation bottlenecks are mathematical, not computational

• Quantum-inspired algorithms deliver value today

• Hybrid classical-quantum systems are the future

• Founder success depends on coachability and balance

‍

Beck Bamberger:

Welcome to Coffee with a Founder. Today we’re joined by Abhishek Chopra, founder and CEOof BQP. You’re building next-generation solutions to solve computational challenges in aerospace and defense using quantum-inspired algorithms. What made you leave academiaand start this company?

‍

Abhishek Chopra:

Thank you for having me. I’m an aerospace engineer and computational scientist by training. During graduate school, I developed large-scale turbulence simulations. One simulation took sixmonths on 250,000 computers.

‍

Industry typically runs thousands of simulations per component. When you multiply that across millions of components, it becomes unsustainable.

‍

That’s when I started asking: how can we make this faster and more practical?

‍

The Compute vs Math Problem

‍

Beck Bamberger:

Is the issue simply that we need more powerful computers?

‍

Abhishek Chopra:

No. That’s the surprising part.

We already have immense compute power. The problem is that the mathematical foundations of these tools haven’t changed in forty years.

Even when I migrated codes from CPUs to GPUs, including work with national labs and NVIDIA, we saw only incremental gains. The algorithms themselves were outdated.

So the bottleneck is math — not hardware.

‍

Quantum-Inspired Approach

‍

Beck Bamberger:

What does quantum-inspired mean in this context?

‍

Abhishek Chopra:

Quantum-inspired algorithms use mathematical frameworks from quantum information science but run on classical hardware like CPUs and GPUs.

Quantum computers will eventually become part of data centers. But they will sit alongside CPUs and GPUs, not replace them.

Today, we can extract significantly more performance from existing infrastructure by improving the mathematics.

‍

Real-World Impact

‍

Beck Bamberger:

Can you share an example?

‍

Abhishek Chopra:

We worked with an aerospace company to redesign aircraft wings. By improving simulation efficiency, they were able to reduce weight, cut fuel costs, and accelerate design cycles.

This is what better math enables.

‍

Founder Growth and Mentorship

‍

Beck Bamberger:

What has been your biggest unlock as a founder?

‍

Abhishek Chopra:

penness and coachability.

Coming from academia, it’s easy to carry pride in science. But building a company requires humility. It requires being open to new business models, pricing strategies, and partnerships.

A mentor once told me: always walk in the path of opening more doors. When making decisions, choose the path that expands opportunity.

That principle still guides me

‍

Work-Life Balance

‍

Beck Bamberger:

How do you sustain this long-term?

‍

Abhishek Chopra:

Entrepreneurship is a marathon. Maintaining health, relationships, and balance is critical.

Professional success matters, but personal well-being sustains the journey.


→ Listen Now

Podcast: The David Daily Show

Quantum computing is transitioning from theory to real aerospace and defense workflows. Inthis episode, Abhishek discusses how quantum-inspired simulations are already solvingcomplex flight challenges, the importance of partnerships like NVIDIA, and why buildingquantum-ready infrastructure today is critical for long-term competitiveness.

→ Listen Now

‍

Key Takeaways

• Quantum-inspired computing already delivers real engineering value

• Aerospace simulation is a leading application domain

• GPU infrastructure is enabling near-term scalability

• Quantum readiness depends on system-level preparation, not just hardware

‍

David Goecke:

Quantum computing is often discussed as a future technology. From your perspective, where are we seeing real-world applications today?

‍

Abhishek Chopra:

We are already seeing value in engineering workflows, particularly in simulation. Instead of waiting for large-scale quantum hardware, we use quantum-inspired algorithms that run on classical systems to solve complex optimization and physics problems.

‍

Quantum in Aerospace Workflows

David Goecke:

What makes aerospace a strong early application area?

‍

Abhishek Chopra:

Aerospace simulations involve extremely complex physics and large datasets. Traditional approaches require significant simplifications. Quantum-inspired methods help reduce computational bottlenecks and allow higher-fidelity modeling.

‍

Infrastructure and GPU Ecosystems

David Goecke:

How important is the role of modern computing infrastructure?

‍

Abhishek Chopra:

It is critical. Advances in GPU computing have enabled us to scale these algorithms effectively. By leveraging high-performance computing systems, we can deliver practical solutions today while building pathways toward future quantum integration.

‍

Preparing for the Quantum Transition

‍

David Goecke:

What should organizations focus on now?

‍

Abhishek Chopra:

They should focus on infrastructure readiness, workforce capabilities, and scalable computational workflows. The transition to quantum computing will be gradual, andpreparation today determines long-term advantage.

‍

→ Listen to the Episode