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USDT De-Peg Probability (30d) (M10122)

Metric IDM10122
Categorytether
Accesspublic
Classificationproprietary
ComputationClassical + Quantum (hardware) + Quantum (simulated)
Computed byBlack Belt Labs
Freshnessfresh
Last refreshed

Calculation methods

MethodLast refreshed
Classical
Quantum (simulated)
Quantum (hardware)

This is a proprietary Madjik metric. Its methodology is a trade secret; the values are available through the API.

Quantum configuration

Every quantum calculation of this metric, with the machine and circuit setup it runs on. Hardware values come from real IBM quantum computers; simulator values from a classical simulation of the same kind of circuit.

MethodQuantum computing on hardware (quant-hw)
ProviderIBM Quantum Platform (Open plan)
Machineibm_marrakesh (156 qubits)
Machine typesuperconducting QPU (IBM Heron)
Qubits used4
Circuits per run1
Shots per run8,192
Circuit depth53
Two-qubit gates12
Gate basiscz, rz, sx, x (IBM Heron native)
Algorithmdirect amplitude readout on hardware (shallow profile)
Profileshallow
Error mitigationdynamical decoupling + measurement twirling; no post-hoc correction
Hardware runs2
Last run2026-10-05T06:30:56
IBM job iddb1k3j2vog1s73fi8bqg
How measuredIBM job record (transpiled circuit stats)
MethodQuantum computing simulated (quant-sim)
ProviderQiskit Aer simulator (IBM open-source software) on Google Cloud
Machineaer_simulator
Machine typeclassical simulator (CPU, noise-free)
Qubits used6
Circuits per run5
Shots per run20,480
Circuit depth2129
Two-qubit gates1216
Gate basisu, cx (Aer, flattened)
AlgorithmMaximum-likelihood quantum amplitude estimation of an empirical tail probability
Profilefull
Error mitigationnone (noise-free simulation)
How measuredrecorded circuits, compiled to u/cx

Personal metrics: figures are the maximum across submitted portfolios (circuit size follows portfolio size). Machine qubits is the size of the whole chip; qubits used is what this calculation needs.

Method comparison (experimental)

The same metric computed several ways on the same frozen inputs, one change at a time, so a gap between two rows has a known cause. Each plus/minus is the standard error of that value. How to read this, and how it scales.

Daily simulator-only comparison

Snapshot 20261016T0002_c1a0fde5 · 2026-10-16 00:02 UTC

StepMethodValue
Classical, exactclassical2.5
Production value (-0.1 h from the snapshot)classical2.5
Quantum simulator, idealquantum simulated2.5
Quantum simulator, ideal (hardware-sized circuit)quantum simulated2.5
Quantum simulator, sampledquantum simulated2.56 ± 0.05129
Noisy device modelquantum simulated2.86 ± 0.05466

Scored against what actually happened

Probability forecast. Outcome: 1 if the USDT peg deviates by more than 1% within the next 30 days. Brier score: lower is better (0 is perfect).

MethodResult
classicalBrier 0.0008702 over 328 forecasts; 0 events; mean forecast 2.9% vs observed 0.0%

Quantum values are not expected to beat the classical value at these problem sizes. The purpose of this section is to show, with uncertainty, how and why the methods differ. Small samples: treat scores as indicative.

Hypotheses monitored by this metric

Access this metric

Query it via the Madjik API:

curl -H "X-API-Key: $MADJIK_API_KEY" \
  https://api.madjik.io/v1/metrics/M10122

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