A COMPILER FOR QUANTUM ADVANTAGE

Q-Day is coming.
Harness it.

Quadv finds where your repository could be sped up by quantum computing, and it translates those algorithms into quantum code.

Use it to harness quantum advantage in your software as soon as hardware catches up.

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Test out the compiler on your own Python file. Run your code on real quantum hardware or a simulator.

Classicalrepo

Quantum
code

An IBM Quantum System One dilution refrigerator — IBM Quantum System One · photo by Onri Jay Benally, CC BY 4.0

Be ready to take advantage of quantum advantage.

Certain quantum algorithms are exponentially faster than their classical analogues. Quantum computing will revolutionize software in:

Quantitative finance
Operations research
Computational physics
Materials science

Quantum hardware will soon be able to perform these speedups at scale. Don't wait to migrate your codebase. Use Quadv, as soon as today.

Upgrade your code. Quantum Physics PhD not needed.

Migrate your repository to a hybrid of quantum and classical code with ease. No specialized training or team required.

↓ INPUT Share your classical code.

lock_code.py brute force · 4096 evals classical

LOCK = 0b100101
def opens_lock(code):
    mixed = code ^ (code >> 6)
    return mixed & LOCK == LOCK
def find_code():
    for code in range(2 ** 12):
        if opens_lock(code):
            return code
    return None
print("unlock code:", find_code())

→

↓ OUTPUT Receive functionally equivalent hybrid code. Run it on real quantum computers or a simulator.

hybrid_lock_code.py amplitude amplification · ~64 ops hybrid

from quadv import runtime as quadv_runtime
from qiskit import QuantumCircuit
LOCK = 0b100101
def opens_lock(code):
    mixed = code ^ (code >> 6)
    return mixed & LOCK == LOCK
def _quadv_oracle_c0():
    qc = QuantumCircuit(12)
    for j in range(6):
        qc.cx(j + 6, j)
    controls = [b for b in range(12) if (LOCK >> b) & 1]
    qc.h(controls[-1]); qc.mcx(controls[:-1], controls[-1]); qc.h(controls[-1])
    for j in reversed(range(6)):
        qc.cx(j + 6, j)
    return qc.to_instruction(label="_quadv_oracle_c0")
def find_code():
    return quadv_runtime.grover_search(_quadv_oracle_c0(), 12, opens_lock)
print("unlock code:", find_code())

Highlighted lines are written by Quadv. The rest is original, classical code.

What Quadv does for you today

Placeholder figures — swap in measured results

algorithm types yield polynomial speedups

in terms of number of operations

100%

of outputted code is machine-verified

(outputs are identical or within stated tolerances)

qubits in circuit-complexity

(available through integration with IBM Quantum hardware)

Maximize your quantum advantage at every stage.

Deterministic reliability

The heart of Quadv is a compiler that translates your classical code into quantum code deterministically. AI agents are integrated as verifiers, not translators, so the tool reliably eliminates your need for specialized quantum software engineers.

Advantage is a moving line

The algorithms worth running on quantum hardware will change with every advancement. As hardware evolves, Quadv writes and rewrites your codebase to be maximally efficient. Integration with all IBM Quantum hardware is already supported.

Speed up your code today.

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Q-Day is coming.Harness it.